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Data Engineer, Global Talent Intelligence

United States, Chicago 119800.00 - 234700.00 USD / Year · Job Posted March 01, 2026
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Job Description

We are hiring a Data Engineer to support the Global Talent Intelligence team. The Global Talent Intelligence (GTI) team sits at the intersection of talent, technology, and strategy—partnering with senior leaders across Microsoft to anticipate market shifts and inform high‑impact business decisions. At the core of this work is a purpose‑built talent data engine that transforms vast, complex external signals into clear, actionable intelligence. As a Data Engineer on GTI, you will drive the next iteration of design and scale for the infrastructure that powers how Microsoft relies on talent movement as a leading indicator of market movement. This role goes beyond traditional data engineering: you will build curated pipelines, models, and power interfaces that enable GTI to move from manual analysis to proactive and predictive insights—unlocking earlier visibility into where skills are emerging, where competition is intensifying, and where strategic intervention matters most. Our GTI data engineer works across an unusually rich and diverse signal ecosystem, synthesizing supply and demand dynamics, competitor and investment signals, innovation indicators, emerging talent and skills, and geo‑specific workforce risk factors. These signals power tools and intelligence products that directly influence executive decision‑making—from workforce planning and site strategy to critical skill investments and long‑term growth bets.This is a highly collaborative role, partnering closely with talent intelligence consultants, analysts, and business stakeholders to ensure data is not only technically sound, but strategically meaningful—moving insights into action.

Job Responsibility

  • Compliance: Anticipates the need for data governance and designs data modeling and data handling procedures
  • Tags data based on categorization
  • Documents data type, build data dictionary, classifications, and lineage
  • Governs accessibility of data within assigned data pipelines
  • Provides guidance on contributions to the data glossary
  • Independently implements data governance and privilege of least access practices
  • Builds responsible AI-compliant data products and/or applications
  • Data Management and Transformation: Plans and creates efficient techniques and operations to transform raw data
  • Independently uses software, query languages, and computing tools to transform raw data
  • Evaluates data to ensure data quality and completeness
  • Merges data into distributed systems, products, or tools
  • Identifies opportunities to leverage and contribute to the development of data tools
  • Writes, implements, and validates code to test storage and availability of data platforms
  • Analyzes relevant data sources
  • Identifies data sources and builds code to extract raw data
  • Contributes to the code review process
  • Uses knowledge of the end-to-end business case to implement orchestration techniques
  • Leverages data protocols, reduction techniques, and aggregation approaches
  • Offers feedback on methods and tools
  • Applies deep knowledge of data to validate that the correct data is ingested
  • Creates a data design document
  • Data Requirements and Modeling: Leads the design of a data model
  • Designs assigned components of the data model
  • Partners with stakeholders to understand the business domain
  • Considers tradeoffs between analytical requirements with compute/storage consumption
  • Demonstrates an advanced understanding of security, performance, and costs
  • Collaborates with appropriate stakeholders across teams
  • Assesses data costs, access, usage, use cases, dependencies
  • Informs clients on feasibility of data needs
  • Negotiates agreements with partners and system owners
  • Proposes new data metrics or measures
  • Defines data source contracts
  • Engineering Fundamentals: Performs root cause analysis
  • Implements and monitors self-healing processes
  • Uses cost analysis to drive product/program level solutions
  • Documents the problem and associated solutions
  • Provides data-based insights into the health of data products
  • Implements and practices both agile and data operations (DataOps) practices
  • Maintains involvement with, and awareness of current and upcoming data engineering practices
  • Writes code to implement performance monitoring protocols
  • Builds visualizations and smart aggregations
  • Develops and updates troubleshooting guides (TSGs) and operating procedures
  • Supports and monitors platforms, analyzing telemetry data
  • Other: Embody our culture and values

Requirements

  • Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years experience in business analytics, data science, software development, data modeling, or data engineering
  • OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering
  • OR equivalent experience
  • 2+ years experience with data governance, data compliance and/or data security
  • Strong data engineering fundamentals, paired with modern AI adoption and automation practices
  • A product mindset for designing systems and interfaces that scale, evolve, and drive action
  • Curiosity about how talent dynamics shape markets, strategy, and competitive advantage
  • The ability to create clarity from complexity and translate insight into direction
  • Dedication to building secure, compliant, and validated data systems
  • Creativity and discipline in designing for optimization, reliability, and scale

Nice to have

  • Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling, or data engineering
  • OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 8+ years experience in business analytics, data science, software development, data modeling, or data engineering
  • OR equivalent experience

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