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To ensure efficient and cost-effective general administration operations through strong vendor management, data-driven reporting, and continuous process improvement.Mô tả công việcOperations Cost ManagementCoordinate procurement of GA services; ensuring cost efficiency and compliance with company policiesSupport budget tracking, expense monitoring, and basic variance analysis across GA categoriesEnsure accurate and timely processing of vendor paymentsAct as a key contact point for day-to-day office administrative mattersData, Reporting AutomationMaintain and manage structured data for admin operations (cost, vendors, usage)Prepare regular reports (weekly, monthly, quarterly) and support dashboard/report enhancementsEnsure accuracy, completeness, and timeliness of admin-related dataAnalyze data to identify trends and provide practical insights to support decision-makingApply Excel and available tools to streamline and improve reporting processesProcess System ImprovementIdentify opportunities to improve admin processes and enhance operational efficiencySupport the development and enhancement of internal systems in collaboration with IT and related teamsParticipate in requirement gathering, user acceptance testing (UAT), and system implementationCoordinate with Team Leader, Manager, and team members to ensure accurate tracking, recording, and reporting of all admin servicesYêu cầu công việcEducation ExperienceBachelor’s degree (preferably in Administration, Accounting, Law or related fields)Minimum 3 years of relevant experienceCore Skills CompetenciesStrong communication and problem-solving skills, with the ability to work effectively across teamsProactive and resourceful in handling issues and driving solutionsHigh attention to detail, especially when working with data and reportsWell-organized with strong planning, prioritization, and time management skillsAbility to manage multiple tasks and meet deadlines in a fast-paced environmentTechnical SkillsStrong Excel skills (data handling, reporting, Pivot Tables, basic formulas)Experience in improving reports or handling moderately complex datasets is preferredFamiliarity with Power Query, VBA, or AI-assisted tools is an advantageWorking Style MindsetResponsible, reliable, and detail-orientedPositive, collaborative, and service-oriented mindsetComfortable working under pressure with a high level of ownership

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).

At MoMo, we are not just processing transactions; we are shaping the future of finance in Vietnam. We are looking for a talented Data Analyst who is passionate about turning raw data into actionable business insights and supporting data-driven decision making across the organization. In this role, you will analyze large volumes of data, build insightful reports and dashboards, and deliver meaningful recommendations to drive business growtMô tả công việc1. Data Analysis Insights Generation: Collect, clean, and analyze data from various sources (transaction data, user behavior, data warehouse, etc.) to support Product, Marketing, Business, and Operations teams. Develop and maintain dashboards and reports (both scheduled and ad-hoc) using SQL and BI tools. Identify trends, patterns, and insights to answer key business questions and propose actionable recommendations. 2. Business Partnership Decision Support: Work closely with Product Managers, Business Leaders, and stakeholders to understand business needs and translate them into analytical solutions. Monitor key performance indicators (KPIs), detect anomalies, and provide early warnings or growth opportunities. Contribute to building and maintaining consistent metrics and semantic definitions across the organization. 3. Data Quality Documentation: Ensure accuracy, reliability, and timeliness of data in reports and analyses. Create clear documentation for dashboards, metrics, and analytical processes. Support data governance initiatives and strictly comply with data privacy, security, and regulatory requirements in the Fintech sector. 4. Continuous Improvement: Optimize SQL queries and analytical workflows for better performance. Collaborate with Data Engineering teams to improve data pipelines and data quality. Stay up-to-date with analytics best practices and emerging tools.Yêu cầu công việcExperience: 2–5 years of experience as a Data Analyst (or similar role). Experience in Fintech, E-commerce, or Internet companies is a strong plus. Technical Skills: Strong proficiency in SQL (advanced query optimization, window functions, complex joins). Hands-on experience with Google BigQuery or other Cloud Data Warehouses. Proficient in BI tools such as Looker, Tableau, or Power BI. Strong ability to leverage AI tools and techniques (e.g., ChatGPT, Claude, Gemini, Copilot, etc.) to boost productivity in data analysis, report generation, code writing, and insight discovery. Soft Skills: Excellent communication skills - ability to present complex insights clearly to both technical and non-technical. Strong business acumen and the ability to connect data analysis with business impact. Comfortable working in a fast-paced, dynamic environment. Mindset: Highly data-driven, detail-oriented, proactive, ownership-minded, and eager to adopt new AI technologies.

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people. The Role: We're seeking a senior developer to join our team. You will design, build, and operate large-scale data and ETL systems that power the firm's research and investment workflows. This is a high-autonomy role - you'll own critical systems end-to-end, make architectural decisions, and deliver solutions with minimal guidance. We need someone who is self-directed, able to lead themselves, take ownership of outcomes, and drive complex problems to resolution independently. You should be comfortable communicating across teams, articulating technical trade-offs to stakeholders, and mentoring others through code review and collaboration. What You'll Do: Design, develop, and own backend services and data pipelines that process large volumes of data optimally and at scale Architect data storage and processing solutions, including schema design, query optimization, and data modeling Build and maintain APIs, messaging systems, and integration layers that connect data producers and consumers Drive technical decisions - evaluate trade-offs, choose the right tools, and define system boundaries Take ambiguous requirements and break them down into deliverable, well-engineered solutions Diagnose and resolve complex production issues - applying strong analytical and systems thinking Improve engineering practices: testing, CI/CD, observability, and documentation What You'll Bring: 8+ years of professional software development experience Strong programming proficiency: Mastery of at least one major programming language (Python, Java, Go, C++, or equivalent). Beyond syntax fluency, you should understand language internals and be able to apply that depth to write performant, reliable code System design: Proven ability to architect distributed, scalable, and fault-tolerant systems. Understanding of common patterns - event-driven architecture, service decomposition, data partitioning, caching strategies Data engineering: Experience building ETL/ELT pipelines, working with batch and streaming data, and handling large-scale data processing Database proficiency: Deep understanding of relational databases (PostgreSQL, MySQL) and familiarity with analytical/columnar stores; strong SQL skills including query optimization Software engineering depth: Strong grasp of data structures, algorithms, design patterns, and software architecture principles - applied in production, not just theory API design: Experience designing clean, well-documented REST/gRPC APIs Incident response mindset: Ability to diagnose production issues methodically, drive root-cause analysis, and feed into post-mortems and operational improvement AI-agent readiness: Openness to working alongside AI coding agents and LLM-powered tools as part of the development workflow - using AI as a force multiplier for code generation, review, debugging, and documentation Nice to Have: Python mastery: Advanced knowledge of Python internals, concurrency (asyncio, threading, multiprocessing), performance profiling, packaging, and strong experience with frameworks such as FastAPI/Flask, SQLAlchemy, pytest, and mypy/type annotations Observability and distributed tracing: Experience with monitoring and observability stacks - metrics, structured logging, distributed tracing (OpenTelemetry, Grafana, ELK) - for diagnosing system behavior and bottlenecks in production DevOps practices: Familiarity with containerization (Docker), CI/CD pipelines (GitLab CI, Jenkins), and infrastructure-as-code (Ansible, Terraform) Programming language versatility: Proficiency in additional languages that complement data platform work - C++ for performance-critical systems, Scala for distributed data processing with Apache Spark, or Rust for high-performance data engineering Team leadership and management: Experience leading a development team, running sprints, conducting code reviews, mentoring engineers, and managing stakeholders' expectations Message queues and streaming: Experience with Kafka, Redis, or similar event-driven architectures Data orchestration: Exposure to Airflow or similar workflow orchestration frameworks Frontend / full-stack awareness: Familiarity with modern web technologies (React, TypeScript) for building internal UIs and dashboards Financial services or quantitative finance background Open-source contributions or a public portfolio of technical work What We Offer: Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday We offer a strong culture of learning and development: training courses, library, speakers, share and learn events Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people Premium Health Insurance and Employee Assistance Program Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family Team building activities every month: Local engagement events – Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc. Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams Happy-hour with tea break, snacks and meals every day in the office! #LI-QM1 By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction. Copyright © 2025 WorldQuant, LLC. All Rights Reserved.WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.

At Aperia, we rely on a dynamic database team. We’re seeking a Database Developer who is ready to work with new technologies and architectures in a forward-thinking organization that’s always pushing boundaries. This person will have SQL development background and SSIS/ETL development experience. The ideal candidate has experience in SQL development, SSRS, SSIS, ETL, Power BI, and Azure Data Factory. Core Responsibilities Designs, builds and implements relational databases.Reviews T-SQL code and performances optimization.Works closely with other members of the business analyst, database administrator and software development, and database development teams, sharing knowledge and making recommendations as needed.Works with offshore development teams and reports.Completes documentation on all assigned systems and databases, including business rules, logic, processes Functional Responsibilities Implement a viable system that can survive and adapt changes demonstrated through delivered projects.Ability to use critical thinking to solve issues that arise.Ability to troubleshoot database performance issues.Ability to deliver successfully tasks and projects independently and be a consultant for others.Ability to do performance tuning: query optimization (avoid coding loop and correlated subqueries), applying indexes and partition functions.Ability to write, debug and test stored procedures, functions, triggers.