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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