Cari Lowongan

At MoMo, we are not just processing transactions; we are shaping the future of finance in Vietnam. We are seeking a visionaryAnalytics Engineering Managerto bridge the gap between complex data infrastructure and actionable business insights. In this pivotal role, you will lead the charge in defining our data modeling standards, ensuring data quality, and empowering our stakeholders with a robust, self-service data platform. If you are passionate about applying software engineering best practices to data analytics and leading high-performing teams, we want you to build the future with usMô tả công việc1. Team Leadership Culture:Lead, mentor, and grow a team of talented Analytics Engineers. You will be responsible for their career development, fostering a culture of continuous learning and technical excellence.Champion the "Data as a Product" mindset, ensuring that datasets produced by the team are treated with the same rigor and reliability as customer-facing software.Drive agile processes within the data team to ensure rapid delivery of value while maintaining high standards.2. Technical Strategy Architecture:Architect and maintain a scalable data modeling layer (using tools likesemantic) that transforms raw data into reliable, documented, and accessible datasets.Define and enforce coding standards, version control practices (Git), and CI/CD workflows for analytics code.Collaborate with Data Engineering to optimize data warehouse performance (e.g., BigQuery/Lakehouse) and manage compute costs effectively.3. Data Quality Governance:Implement automated testing and observability frameworks to detect data issues before they impact downstream users.Establish clear data lineage and documentation to democratize data access across the organization.Ensure strict adherence to data privacy, security, and compliance standards—a critical requirement in the Fintech sector.4. Cross-Functional Collaboration:Partner closely with Product Managers, and Business Leaders to translate complex business requirements into technical data solutions.Act as a technical advisor, helping stakeholders understand the "art of the possible" with our data stack.Yêu cầu công việcExperience:5+ years of experience in the Data domain, with at least 2 years in a leadership or management role.Technical Mastery:Expert-level SQL skills and deep understanding of query optimization.Hands-on experience with Cloud Data Warehouses (Google BigQuery)Workflow Orchestration:Hands-on experience with orchestration tools such asAirflow, n8n.You should be capable of designing complex, dependency-aware pipelines that are resilient to failure.BI Semantic Layer Integration:Deep understanding of how data is consumed by BI tools (e.g.,Looker...). Ability to design the 'Semantic Layer' to ensure consistent metrics across the organization.Soft Skills Culture FitStakeholder Management:"Ability to manage expectations with C-level executives and negotiate priorities effectively in a fast-paced environment."Talent Acquisition:"Experience in recruiting top-tier engineering talent and building a diverse, high-performing team from the ground up."

At MoMo, we are not just processing transactions — we are building the data intelligence layer that powers smarter decisions across Vietnam's leading fintech platform.We are looking for a Senior Data Analyst who goes beyond reporting: someone who proactively hunts for high-value problems, builds AI-driven data agents, and translates complex data into strategies that move the business. In this role, you will work at the intersection of analytics, automation, and business strategy — partnering closely with product, ML, and business teams to deliver insights that matter.If you are passionate about turning data into real impact and raising the bar for the analysts around you, we want you to build the future with us.Mô tả công việcYou bring deep technical skills and a product-minded approach to data — comfortable going from raw data to a deployed agent to a boardroom recommendation. You think in systems, not just queries: designing agentic workflows that automate decisions, reduce manual overhead, and scale analytical impact far beyond what any single analyst could deliver alone.Proactively identify and scope high-value analytical problems; deliver insights and strategies that drive measurable business outcomes.Design and ship production-ready data agents that automate repetitive workflows and scale analytical capacity across the team.Build forecasting models and KPI frameworks that support real operational and business planning decisions.Own data solutions end-to-end — reliable, documented, and reusable across stakeholdersMentor peers and contribute to team knowledge through internal sharing and continuous learning.Yêu cầu công việc3+ years as a data analyst, analytics engineer, or equivalentAdvanced SQL and Python — data wrangling, modeling, pipeline workHands-on experience building AI agents or automated data workflowsFamiliar with semantic/metrics layers (metric definitions, dimensions) to ensure consistency across analyses and dashboards"Data as a Product" mindset — you build data solutions that are reliable, documented, and reusableStrategic communicator — translates complex findings into clear business recommendationsSelf-directed, outcome-oriented, and collaborative by default

Mô tả công việcBuilding Machine Learning models using your core expertise;Collaborate with Product and Business to define the Machine Learning product, focus on Personalization and Financial Services;Collecting, cleaning, preparing data at large scale for modeling;Adding new features, exploring new approaches to keep pushing the model performance;Participating in productionizing Machine Learning models for live production;Designing, conducting A/B tests and analyzing the results for experiment insights;Building pipelines for continuously validating and updating models.Yêu cầu công việcBachelor’s degree in Computer Science, Engineering, or related fields;4+ years working experience with 2 years hands-on with ML, or 2+ years with Ph.D. degree;Good understanding of mathematical foundations of Machine Learning algorithms;Have practical experience in applying Machine Learning in personalization, credit scoring or user behavior analysis;A builder. You go the extra mile to bring your prototypes to production;Strong product ownership. You take a high responsibility for what you build. You keep a high bar for product quality;Strong collaboration skills. You reach out to help other team members;Experience with credit scoring or financial service models is a plus.

Mô tả công việcBuilding Machine Learning models using your core expertise;Collaborate with Product and Business to define the Machine Learning product, focus on Fraud/Risk management and Financial Services;Collecting, cleaning, preparing data at large scale for modeling;Adding new features, exploring new approaches to keep pushing the model performance;Participating in productionizing Machine Learning models for live production;Designing, conducting A/B tests and analyzing the results for experiment insights;Building pipelines for continuously validating and updating models.Yêu cầu công việc3+ years working experience with 2 years hands-on with ML, or 2+ years with PhD degree;Good understanding of mathematical foundations of Machine Learning algorithms;Have practical experience in applying Machine Learning in Fraud/Risk management, credit scoring or user behavior analysis;A builder. You go the extra mile to bring your prototypes to production;Strong product ownership. You take a high responsibility for what you build. You keep a high bar for product quality;Strong collaboration skills. You reach out to help other team members; Familiar with using genAI in analytics/modeling and coding;Experience with financial service models is a plus.

Mô tả công việcDesign and implement statistical models, machine learning algorithms, and data pipelinesto solve business problems;Collaborate with Product and Business to define the Machine Learning product, with afocus on recommendation systems, ranking algorithms, and classification models;Collecting, cleaning, preparing data at large scale for modeling;Analyzing large datasets to surface actionable insights and translate them intomeaningful, production-ready features;Experimenting with new modeling approaches and feature strategies to continuously pushperformance;Participating in productionizing Machine Learning models for live production;Designing, conducting A/B tests and analyzing the results for experiment insights;Building pipelines for continuously validating and updating models;Communicating findings and model outcomes clearly to both technical and non-technicalstakeholders, driving data-driven decisions across teams.Yêu cầu công việc3+ years working experience with 2 years hands-on with ML, or 2+ years with PhD degree;Good understanding of mathematical foundations of Machine Learning algorithms;Have practical experience in applying Machine Learning in recommendation systems,ranking, classification, or clustering problems (e.g. personalization, search ranking, contentfiltering, customer segmentation, or user behavior modeling);Strong analytical mindset — able to go beyond model metrics and extract businessinsights from data that directly inform product and strategy decisions;Solid experience in feature engineering: identifying, designing, and validating featuresgrounded in domain knowledge and data exploration;A builder. You go the extra mile to bring your prototypes to production;Strong product ownership. You take a high responsibility for what you build. You keep ahigh bar for product quality;Strong collaboration skills. You reach out to help other team members;Familiar with using genAI in analytics/modeling and coding;Experience with large-scale ranking or retrieval systems is a plus.

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 monitoring;Machine learning products including recommendation systems, personalization, risk scoring, fraud detection, targeted promotions, and financial services;We're also building a next-generation hybrid data platform across multiple cloud providers, giving us greater control over both cost and technology.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 mechanisms;Developing and deploying resilient data pipelines across the data lake, data warehouse, and streaming systems;Delivering 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 data;Monitoring 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 outputs;Tracking and optimising resource usage for efficiency;Additionally, 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 platform;Explore the MoMo data ecosystem independently;Provide a single source of truth with high data quality to downstream consumers;Track and manage infrastructure costs across major projects, teams, and departments.Yêu cầu công việcBachelor’s degree in Computer Science, Engineering, or a related field;A problem solver with a strong sense of ownership and accountability — not just a task executor;5+ years of experience working as a Data Engineer and 1+ year of experience working as leader;Curious and committed to lifelong learning, with a passion for solving business problems through engineering, improving service quality and usability, and maintaining a strong customer focus;Strong foundation in computer science fundamentals, including data structures, algorithms, database systems, and data modelling techniques;Proficient in at least one of the following languages: SQL, Python, JVM-based languages;Experience with databases such as PostgreSQL, MySQL, ClickHouse, DuckDB, etc;Skilled in analysing, designing, implementing, and optimising Data Vault or Dimensional Modeling for performance and cost;Hands-on experience with infrastructure platforms — cloud-based (e.g., GCP, AWS) or on-premise — and container orchestration using Kubernetes;Experience with data storage and processing engines like Apache Spark, Apache Flink, and StarRocks;Experience with Google Cloud Platform or Amazon Web Services is a plus.

BI Data Modeling: Design scalable data marts and build end-to-end pipelines from raw data to business-ready tables, ensuring reliability, performance, and standardized metrics (e.g., GMV, conversion, DAU).Demand Growth Analysis: Analyze demand trends, identify growth levers, and lead A/B testing end-to-end–from hypothesis to evaluation and monitoring.Dashboard report  Insights: Develop dashboards and reports, deliver ad-hoc analyses, and translate complex data into clear, actionable insights for stakeholders.Continuous Improvement Mentorship: Enhance BI processes using advanced tools (incl. AI) and mentor junior members to build team capability and drive continuous improvement.

We are seeking a senior market intelligence analyst with strong analytical skills and business mindset. The preferred candidate will be the strategic radar for our merchant strategy. They will transform complex internal and external data into actionable insights that dictate our competitive edge in terms of merchant assortment, merchant investment, price competitiveness and market share.1. Competitive Intelligence Market benchmarkingExternal Benchmarking: Monitor and interpret complex data to track competitor assortment, coverage percentage and growth trend by location and segment in order to identify critical assortment gaps.Commercial metric tracking: Conduct cross-platform comparisons of merchant investment, take-rate structures, and promotion participation across different segments and cities.Market Share Research: Liaise with BD teams to conduct field research and data modeling to estimate market share, flagging alarming trends and identifying untapped room for growth.Project management: conduct and oversee end-to-end cross-functional researches deep-dive into merchant sentiment, feature adoption investment willingness.2. Merchant strategy supportMerchant Strategy Development: Analyze merchant hygiene and performance factors—such as opening hours, ratings, and category —to guide high-level strategic decisions.Growth Lever Identification: Execute deep-dive analyses and build heatmap to highlight areas for merchant acquisition and expansion.Operational Mechanics: Maintain a deep understanding of merchant ops policies and funding mechanics, via both primary and secondary research3. Dashboard ReportingAdvanced Data Visualization: Develop and maintain dashboards, reports, and data visualizations to monitor key performance and business metrics (Excel/SQL-based) that provide at-a-glance clarity on key business metrics.Proactive Anomaly Detection: take ownership in data usability and Investigate outliers within cleaned datasets to ensure reporting accuracy.AI-Driven Productivity: Champion the use of in-house and external AI solutions to automate routine tasks, summarize market trends, and improve productivity and analytical capabilities.

In a Financial Services context, data carries weight in financial accuracy and regulatory compliance: reconciliation, audit trail, PII handling, regulatory reporting. The models you build are not only the source for dashboards and reports, but also the semantic foundation for internal AI products — specifically a natural-language-to-SQL data assistant. A clearly defined, well-documented model layer is the prerequisite for the agent to generate accurate SQL.Mô tả công việcDevelop and maintain data transformation models in a layered architecture (staging → intermediate → marts), applying dimensional modeling (star schema, slowly changing dimensions) and medallion-style layering. Write SQL transformations optimized for the warehouse: understand materialization strategy (view vs table vs incremental), partitioning / clustering, and query cost — not just "correct" but "efficient". Build and maintain data quality tests (not-null, unique, relationship, accepted-values, freshness) and assertions; investigate root cause and resolve test failures. Document models, columns, and business logic as code (data dictionary, lineage) so both humans and the AI assistant can interpret them — documentation is part of the artifact, not an afterthought. Own the metrics / semantic layer for assigned domains: standardize metric definitions (e.g. disbursed amount, GMV, NPL, conversion rate) so each metric has a single source of truth, avoiding the "every report shows a different number" problem. Participate in code review via the Git/Gerrit workflow: follow branching, change-management, and CI conventions. Collaborate with DA, BA, Product, and Finance to translate business requirements into data models; work with DE on upstream data contracts. Monitor model/pipeline freshness and reliability; participate in data incident triage and contribute to data reliability governance initiatives. Yêu cầu công việcMust-have1–3 years working with dataStrong SQL: joins, window functions, CTEs, aggregation; able to read/write complex queries and reason about both correctness and performance.Solid grasp of data modeling fundamentals: fact vs dimension, grain, normalization vs denormalization, and when to use which.Version control with Git: branch, commit, merge/rebase, resolve conflicts; understands the code review workflow.Basic Python for data manipulation / scripting.Analytical mindset: able to decompose an ambiguous business question into a clear data structureNice to havedbt experience (models, tests, macros, snapshots, docs) — strong plus. Cloud data warehouse experience: BigQuery / Snowflake / Redshift / Databricks. Familiarity with orchestration (Airflow / Dagster) and the ELT paradigm. FS/fintech domain knowledge: lending, payments, banking, risk metrics. BI tools: Looker, Metabase, Superset, Power BI. Understanding of data governance, PII sensitivity, and regulatory reporting. Exposure to AI/LLM tooling for data (semantic/metric layers powering NL-to-SQL).

We are looking for an exceptional Full-stack Developer to join our forward-thinking engineeringteam. In this role, you will be at the forefront of our architectural evolution, driving thedevelopment of scalable, modern web applications.You will not just be a contributor; you will be a key architect in our shift towards aMicro-frontend architecture. We value engineers who are eager to embrace modernmethodologies, including Prompt Driven Development, to maximize efficiency and innovation.If you are passionate about decoupling complex systems, designing robust APIs, andleveraging AI to accelerate your workflow, we want to hear from you.Mô tả công việcMicrofrontend Architecture: Design, develop, and maintain loosely coupled micro-appsusing Single SPA. Ensure seamless integration and shared state management across theplatform.Backend Development: Build scalable, maintainable, and high-performance server-sideapplications using NestJS and MongoDB.State Data Management: Implement sophisticated state management and cachingstrategies utilizing Redux Toolkit, Redux Toolkit Query, and Tanstack React Query to ensurea snappy user experience.UI/UX Implementation: Craft responsive and accessible interfaces using Ant Design, AntDesign Pro Components, and Radix UI.Prompt Driven Development: Actively utilize and advocate for AI-assisted tools (LLMs,Copilot) to generate boilerplate, debug complex issues, and accelerate the developmentlifecycle.Code Quality: Write clean, testable, and documented code. Participate in code reviews tomaintain high standards.Yêu cầu công việcFrontend StackMicrofrontends: extensive experience with Single SPA is a critical requirement for this role.Data Fetching: Experience with Redux Toolkit Query or Tanstack React Query.UI Libraries: Proficiency with Ant Design, Ant Design Pro Components, and Radix UI.Backend StackFramework: Solid experience building RESTful or GraphQL APIs with NestJS.Database: Proficiency in data modeling and querying with MongoDB.Experience Level:Middle/Senior: Proven track record of delivering complex full-stack applications (typically4+ years of experience).Soft SkillsSystem Design Thinking: You understand the trade-offs in distributed systems and candesign architectures that are scalable and maintainable (Crucial for our Microfrontendapproach).Mentorship Knowledge Sharing: You enjoy helping others grow. You proactively shareknowledge, conduct code reviews, and mentor junior team members.Problem-solving Adaptability: You approach challenges with a solution-oriented mindsetand can adapt quickly to changing requirements or technologies.Effective Communication: You can articulate complex technical concepts to both technicaland non-technical stakeholders clearly and concisely.Nice to HaveDemonstrated experience or a strong interest in integrating AI tools into your daily codingworkflow to boost productivity and code quality.