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Minimum qualifications: Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience. 1 year of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume). Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript. Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams. Preferred qualifications: Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments. Experience working with Big Data, information retrieval, data mining, or machine learning. Experience in building multi-tier high availability applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow). Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments. About the jobAs a Data Engineer for the Enterprise Platforms team, you will play a vital role in building and maintaining the data infrastructure that fuels our product strategy. You will design, develop, and optimize data pipelines, ensuring data quality and accessibility for advanced analytics. Your technical expertise will enable the product team to leverage data-driven insights to optimize product feature adoption and performance and measure the impact of strategic initiatives. To accelerate the growth and market leadership of Enterprise Buying Platforms (DV360 and SA360), you will answer critical business questions and deliver actionable, data-driven insights that inform product and commercial strategy. The Enterprise Platform Data Science team provides quantitative support, market understanding and a strategic perspective to our partners throughout the organization, in close collaboration with the Ads Commerce Finance team.Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale. Responsibilities Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders. Design, develop, and maintain scalable and reliable data pipelines to collect, process, and store data from various data sources. Implement robust data quality checks and monitoring to ensure data accuracy and integrity. Collaborate with cross-functional teams (data science, engineering, product managers, sales and finance) to understand data requirements and deliver impactful data solutions. Optimize data infrastructure for performance, efficiency, and scalability to meet evolving business needs. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience. 3 year of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume). Experience with database administration techniques or data engineering, and writing software in Java, C++, Python, Go, or JavaScript. Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams. Preferred qualifications: Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments. Experience working with Big Data, information retrieval, data mining, or machine learning. Experience in building applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow). Experience architecting, developing software, or production-grade Big Data solutions in virtualized environments. About the jobAs a Data Engineer for the Analytics, Insights and Measurement (AIM) team, you will Help customers, grow their businesses through trusted analytics, insights and measurement that ensure user privacy.Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.Responsibilities Create and deliver recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders. Design, develop, and maintain reliable data pipelines to collect, process, and store data from various data sources. Implement data quality checks and monitoring to ensure data accuracy and integrity. Collaborate with cross-functional teams (data science, engineering, product managers, sales and finance) to understand data requirements and deliver data solutions. Enhance data infrastructure for performance, efficiency to meet evolving business needs. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google’s technology, platforms and people and we welcome Indigenous applicants. Please see our Reconciliation Action Plan for more information.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sydney NSW, Australia; Melbourne VIC, Australia.Minimum qualifications: Bachelor's degree or equivalent practical experience. 10 years of experience in software engineering, software infrastructure engineering, security, big data and analytics, cloud computing, or cloud networking. Experience with infrastructure, storage, platforms and data, as well as the cloud market and customer buying behavior. Experience engaging with, and presenting to, technical stakeholders and executive leaders. Preferred qualifications: Experience in technical sales or consulting in cloud computing, data analytics, and big data. Experience with architecture design, implementing, tuning, schema design and query optimization of scalable and distributed systems. Experience with developing data warehousing, data lakes, batch/real-time event processing, streaming, data processing (ETL/ELT), data migrations, data visualization tools, and data governance on cloud native architectures. Understanding of customer requirements with the ability to break down requirements and design technical architectures. About the jobWhen leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products. As a Practice Customer Engineer (CE) with a specialty in Data Analytics, you will partner with technical sales teams to differentiate Google Cloud to our customers. You will serve as a technical expert responsible for accelerating technical wins and adoption of complex, specialized workloads. You will leverage your deep expertise in our most strategic product areas, in partnership with Platform CEs, to perform designing of data foundation architectures and develop MVPs (Minimum Viable Products) to promote new, highly specialized solutions to customers. You will solve analytics-centered customer challenges and provide a critical feedback loop to unblock customers and influence product development. You will leverage excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Drive the technical win for complex workloads within data analytics to ensure rapid and successful adoption, primarily supporting the business cycle from use case identification, technical evaluation, and through customer ramp. Combine business strategies, development and prototyping to provide functional, customer-tailored solutions that secure buy-in from customer domain experts. Provide deep technical consultation to customers, acting as a technical advisor and building lasting customer relationships. Leverage learnings from customer engagements to contribute to reusable solutions and assets with the Go-To-Market team. Provide critical feedback from customer engagements to Product and Engineering teams to improve architectures and solutions. Work within product and engineering management systems to document, prioritize and drive resolution of customer feature requests and issues. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

MoMo is the market leader in mobile payments in Vietnam, driven by a commitment to enhancing the lives of Vietnamese citizens through technological innovation.Within the MoMo BigData AI department, we prioritize Smart, Efficient, and Excellent execution. We are currently undergoing a major transformation to build a new hybrid data platform spanning multiple cloud vendors (GCP AWS).We are seeking an experienced Data Engineer to help us architect this platform to optimize for both budget control and technological flexibility. You will play a pivotal role in shifting our mindset from "managing data" to creating valuable Data Products that empower our internal consumers.Mô tả công việcWith MoMo's AI-first mission, we are designing and building a self-serve data platform to empower both internal teams and external partners. This platform allocates resources based on users’ needs to support:Ingesting data from diverse sources — either in batch or streaming, using both pull and push mechanismsDeveloping and deploying resilient data pipelines across the data lake, data warehouse, and streaming systemsDelivering high-quality, derived datasets to downstream tools such as BI solutions (e.g., Apache Superset,Looker Data Studio), via multiple delivery methods including APIs, datasets, and streaming dataMonitoring data quality throughout all data pipelines in the platform to ensure high-quality data, resulting in better decision-making, accurate reporting, and reliable machine learning outputsTracking and optimising resource usage for efficiencyAdditionally, we are building Data Management Systems that enable the Data Governance team and data consumers to:Manage the full data lifecycle within the big data platformExplore the MoMo data ecosystem independentlyProvide a single source of truth with high data quality to downstream consumersTrack and manage infrastructure costs across major projects, teams, and departmentsYêu cầu công việcThe MindsetPassion for Data: You dream in SQL ("SELECT COUNT(SHEEP)...") and care deeply about data accuracy.Product Thinking: You view data as a product, focusing on the usability and reliability of what you deliver to stakeholders.The Tech StackStrong Coding Skills: Proficiency in Java/Kotlin (for robust backend services) and Python (for data processing/scripting).Hybrid Cloud Infrastructure: Hands-on experience with GCP. Proficiency in Kubernetes, Docker, and IaC tools like Pulumi or Terraform.Big Data Engines: Deep understanding of computing engines like Spark, Trino, BigQuery, and Clickhouse.Orchestration: Experience building DAGs and workflows in Airflow or Temporal.Data Sources: Familiarity with diverse sources including App Events, CDC from transactional DBs (Oracle, MySQL, MSSQL), and streaming systems (Kafka, PubSub).Soft SkillsStrong problem-solving abilities with a focus on root-cause analysis.Collaborative spirit: You can explain complex infrastructure decisions to non-technical stakeholders.

MoMo is the leading mobile payments provider in Vietnam, committed to improving the lives of every Vietnamese through technological innovation. As our business continues to expand, we're looking for an experienced Data Engineer to join our Data Platform team.At MoMo, we emphasize smart, efficient, and excellent execution, with a strong focus on data quality. Our data platform delivers critical insights for:Business and app performance monitoringMachine learning products including recommendation systems, personalization, risk scoring, fraud detection, targeted promotions, and financial servicesWe're also building a next-generation hybrid data platform across multiple cloud providers, giving us greater control over both cost and technologyMô tả công việcWith MoMo's AI-first mission, we are designing and building a self-serve data platform to empower both internal teams and external partners. This platform allocates resources based on users’ needs to support:Ingesting data from diverse sources — either in batch or streaming, using both pull and push mechanismsDeveloping and deploying resilient data pipelines across the data lake, data warehouse, and streaming systemsDelivering high-quality, derived datasets to downstream tools such as BI solutions (e.g., Apache Superset, Google Data Studio), via multiple delivery methods including APIs, datasets, and streaming dataMonitoring data quality throughout all data pipelines in the platform to ensure high-quality data, resulting in better decision-making, accurate reporting, and reliable machine learning outputsTracking and optimising resource usage for efficiencyAdditionally, we are building Data Management Systems that enable the Data Governance team and data consumers to:Manage the full data lifecycle within the big data platformExplore the MoMo data ecosystem independentlyProvide a single source of truth with high data quality to downstream consumersTrack and manage infrastructure costs across major projects, teams, and departmentsYêu cầu công việcBachelor’s degree in Computer Science, Engineering, or a related fieldA problem solver with a strong sense of ownership and accountability — not just a task executor5+ years of experience working as a Data Engineer and 1+ year of experience working as leaderCurious and committed to lifelong learning, with a passion for solving business problems through engineering, improving service quality and usability, and maintaining a strong customer focusStrong foundation in computer science fundamentals, including data structures, algorithms, database systems, and data modelling techniquesProficient in at least one of the following languages: SQL, Python, JVM-based languagesExperience with databases such as PostgreSQL, MySQL, ClickHouse, DuckDB, etcSkilled in analysing, designing, implementing, and optimising Data Vault or Dimensional Modeling for performance and costHands-on experience with infrastructure platforms — cloud-based (e.g., GCP, AWS) or on-premise — and container orchestration using KubernetesExperience with data storage and processing engines like Apache Spark, Apache Flink, and StarRocksExperience with Google Cloud Platform or Amazon Web Services is a plus.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience in product management or related technical role. 3 years of experience taking technical products from conception to launch (e.g., ideation to execution, 0 to 1, etc). Experience developing or launching products or technologies within databases, analytics, big data, or a related area. Experience in Apache Spark for data processing. Preferred qualifications: Experience driving product goal, go-to-market strategy, and design discussions. Experience working on developer tools or open source projects. Experience with data analytics tools (Hadoop, Spark), project involvement, and committership. Ability to drive results in collaborative, cross-functional environments with minimal oversight. About the jobAt Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day. In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users. In this role, you will be responsible for Google Cloud Platform (GCP) Data Analytics' big data analytics portfolio for Spark and other open source components in Dataproc and Serverless Spark.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Drive the new set of innovation and growth powering Open Source Analytics at scale on Google Cloud. Work closely with customers, field and partners to address unmet need. Partner with business development and GTM teams to build growth strategies. Partner with engineering, research and key stakeholder teams to align roadmap and Objectives and Key Results (OKRs). Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Astera Labs (NASDAQ: ALAB) provides rack-scale AI infrastructure through purpose-built connectivity solutions. By collaborating with hyperscalers and ecosystem partners, Astera Labs enables organizations to unlock the full potential of modern AI. Astera Labs’ Intelligent Connectivity Platform integrates CXL®, Ethernet, NVLink, PCIe®, and UALink™ semiconductor-based technologies with the company’s COSMOS software suite to unify diverse components into cohesive, flexible systems that deliver end-to-end scale-up, and scale-out connectivity. The company’s custom connectivity solutions business complements its standards-based portfolio, enabling customers to deploy tailored architectures to meet their unique infrastructure requirements. Discover more at www.asteralabs.com.Job Description Astera labs is seeking a skilled and motivated Data Scientist. This individual will play a pivotal role in identifying key data points for collection, developing strategies to accumulate data and deriving actionable insights an anomaly based on a solid foundation of relevant know-how. Also, will also be responsible for creating, testing, and deploying scripts and methods for data collection and analysis to support decision-making. The Engineer will collaborate with cross-functional teams to identify critical data sources to determine the most effective data collection strategies, will develop automated and scalable data collection pipelines, will ensure data quality, integrity, and consistency across all sources and may use AI techniques to refine the results toward failures predictions. Basic Qualifications Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, or a related field. Advanced degrees in data science or Machine learning / AI - Advance. Proficiency in programming languages such as Python, R, or MATLAB. Strong understanding of data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Understanding of high speed interfaces such as Ethernet, PCI-E , WiFi. Experience with data visualization tools such as Tableau, Matplotlib, Graphana. Strong analytical and critical-thinking skills to identify patterns and outliers. Customer-obsession, Think and act with the customer in mind! Goal-driven, Self-motivated, be able to work independently and with teams with people around the globe. Entrepreneurial, open-minded behavior and can-do attitude. Required Experience Experience with data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Machine learning and AI techniques and frameworks (e.g., TensorFlow, Scikit-learn). Proven ability to manage multiple tasks and meet deadlines. Preferred Experience Embedded Firmware development with C-language, scripting with Python or other equivalent programming languages. Master’s degree in a relevant field. Experience with cloud platforms (e.g., AWS, Azure, GCP) for data storage and processing. Familiarity with big data technologies (e.g., Hadoop, Spark). Knowledge of engineering design tools and processes. We know that creativity and innovation happen more often when teams include diverse ideas, backgrounds, and experiences, and we actively encourage everyone with relevant experience to apply, including people of color, LGBTQ+ and non-binary people, veterans, parents, and individuals with disabilities.

Google welcomes people with disabilities.Minimum qualifications: Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 5 years of experience with two or more of the following: Web Tech, Data/Big Data, Machine Learning, Systems Admin, Networking, Kubernetes. 5 years of experience reading or debugging code in one or more general purpose languages (e.g. Python, Java, Go, C or C++). Ability to communicate in Japanese and English fluently to communicate with external and internal stakeholders. Preferred qualifications: Experience with SQL database administration, open source software communities, cloud networking solutions, or distributed computing. Experience in data analytics, warehousing, Extract Transform and Load (ETL) development, data science, or other Big Data applications. Experience working with recommendation engines, data pipelines, or distributed machine learning. Experience working in distributed applications or micro-services in a cloud based environment (e.g., Docker, Kubernetes). Experience working in a fluid environment with cross-collaboration across functions. Knowledge of Web application development/deployment, HTTP/RESTful API troubleshooting, or database design/troubleshooting. About the jobThe Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You solve the technical issues to show how our products can make businesses more collaborative. You work with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are important in helping Google grow its cloud business and helping companies around the world innovate.Responsibilities Develop an understanding of Google Cloud's Data Analytics (e.g. BigQuery), AI/ML, and underlying architectures by troubleshooting, reproducing, and determining the root cause for customer reported issues, building tools, and diagnosis. Act as a consultant and subject-matter-expert for internal stakeholders in Engineering, Sales, and customer organizations to resolve technical deployment obstacles and improve Google Cloud. Work as a part of a team of Engineers/Consultants that globally ensure 24 hour customer support. This may include a need to sometimes work non-standard work hours or shifts. Understand customer issues, advocate for their needs with internal teams, including Product and Engineering teams, and drive production. Work with customers on their production deployment to resolve issues and achieve product readiness and availability. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google’s technology, platforms and people and we welcome Indigenous applicants. Please see our Reconciliation Action Plan for more information.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sydney NSW, Australia; Melbourne VIC, Australia.Minimum qualifications: Bachelor's degree or equivalent practical experience. 10 years of experience with cloud native architecture in a customer-facing or support role. Experience in pre-sales or field engineering at an enterprise technology company, or similar customer facing experience. Experience engaging with, and presenting to, technical stakeholders and executive leaders. Experience in pre-sales management or people management on a data analytics-related or technical team. Experience with data analytics technologies or concepts, cloud, and on-premise technologies. Preferred qualifications: Experience influencing cross-functional teams (e.g., Product Management, Engineering, Sales), customers, and partners to impact business goals, customer experience, and customer expansion. Experience tailoring and delivering compelling messages to audiences, asking strategic questions, and leading conversations that drive business opportunity. Specialization in "Big Data," including analytics warehousing, data processing, data transformation, data governance, data migrations, ETL, ELT, SQL, NoSQL, performance or scalability optimizations, or batch versus streaming. Thought leader in data analytics and adjacent practice areas, specialized in technical sales and strategizing around holistic customer and industry solutions. About the jobWhen leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products. Specialist Customer Engineers seek to accelerate Google Cloud customer success by providing domain-specific technical expertise, while responsibly influencing products and solutions.As a Customer Engineering (CE) Manager, you lead and deploy a team of subject matter experts responsible for working alongside our customers to provide trusted technical and solution advice to accelerate workload migration and remove technical impediments.Applicants must have a right to work in Australia as Google is currently unable to sponsor a visa for this position.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Lead a team of technical experts in a matrixed organization. Focus on talent strategy, assessing go-to-market readiness and gaps in CE preparedness, skills development, and opportunity coverage to deliver successful cloud transformation outcomes for customers and accelerate business goals. Execute the technical vision and strategy for your region’s data analytics practice. Lead the broader region's data analytics technical community, to ensure sub-regional technical contributions, achieve scale through artifact and innovation sharing. Influence cross-functional teams, including Product Management and Engineering, ensuring customer needs are represented in product roadmaps and new technology is incubated and scaled. Lead technical engagements with strategic customers, working with cross-functional peers to plan customer engagements. Travel up to 25% to customer sites, conferences, and other related events as required, acting as a public advocate for Google Cloud. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 10 years of experience working with data infrastructure and data models by performing exploratory queries and scripts. 5 years of experience coding in one or more programming languages, and designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal and external stacks. 3 years of experience in a people management, supervision, or team leadership role. Preferred qualifications: 8 years of experience in data analysis, database querying (e.g., SQL), and BigQuery. 5 years of experience with statistical methodology and data consumption tools such as business intelligence tools, collabs, jupyter notebooks, Tableau, Power BI, Data Studio, and business intelligence platforms. 5 years of experience in a leadership role with direct reports. Experience with a wide range of data engineering and data governance tools like cloud platforms, data warehousing solutions, data quality tools, and metadata management systems. Experience with data analysis at scale, including statistics, and machine learning model development. Familiarity with data center technology or supply chain. About the jobThe Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You listen to the customer and swiftly problem-solve technical issues to show how our products can make businesses more productive, collaborative, and innovative. You work closely with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are crucial in helping Google grow its Cloud business and helping companies around the world innovate. The Cloud Supply Chain Data Engineering, End-to-End Systems and Analytics team is chartered to provide the most efficient systems and analytics enabling faster decision making and throughput time for Google Cloud's Supply Chain. As Google Cloud continues to scale, this team’s work will contribute to the ongoing product, process and capability growth to ensure Google can continue to meet market and competitive goals.Google's projects, like our users, span the globe and require managers to keep the big picture in focus. As a TPM, Data Engineering, you will lead the next generation of business intelligence platforms, reporting, and intelligence globally for Google's Server Operations teams. You will work with internal and external customers to build cascading dashboards and reports, diagnostic analytics, and owning a server operations measurement framework for effective decision making.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Lead a team of individuals. Set and communicate individual and team priorities that support organizational goals. Meet regularly with individuals to discuss performance and development, and provide feedback and coaching. Design and build data processing systems with a particular emphasis on security, compliance, scalability, efficiency, reliability, and portability. Create or consult in creating data visualizations using Business Intelligence (BI) tools (e.g., Data Studio, Tableau, etc.). Develop and maintain data models, pipelines, and exchange formats to assist in the visualization, analysis, and interpretation of data and for use of data in ML training/models. Provide ongoing support for data users through maintenance of reports, queries, and dashboards, fielding user questions, authoring documentation, and delivering training. Develop tools and systems to automate data processes, facilitate faster turnarounds, and increase overall efficiency. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.