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Data Engineering is the production engine behind Global Skilling's data-driven decisions. The team delivers a unified, secure, and governed data platform that enables reporting, insights, data products, and downstream consumption across Microsoft. We are hiring multiple Data Engineer II roles across several focus areas. Each role contributes to a different layer of the WISE data ecosystem — from foundational data pipelines and governance, to Data-as-a-Service products, to reporting and analytics experiences.
Job Responsibility
Build and maintain production ETL pipelines ingesting data from 1st-party, 2nd-party, partner, and 3rd-party sources
Design and implement data-sharing patterns and access controls (RBAC) across organizational boundaries
Contribute to data mesh patterns, including data contracts, domain-owned datasets, and product-style publishing
Develop and maintain data governance solutions, including lineage, cataloging, data quality, and compliance
Design, build, and operate REST APIs and backend services that expose WISE datasets as data products
Define and manage API contracts, including schema design, versioning, and lifecycle management
Build serving layers supporting low-latency, request-response data access
Design and deliver Power BI semantic models, curated datasets, and reporting solutions
Build and support self-serve analytics experiences, including discoverability and performance optimization
Instrument pipelines and services through observability practices (metrics, logs, traces)
Partner with Privacy, Security, and platform teams to ensure data protection and compliance
Contribute to AI-ready data patterns, including pipelines, APIs, and reporting systems designed for agentic or Copilot-based consumption
Participate in code reviews, design discussions, documentation, and on-call rotation
Embody our Culture and Values
Requirements
Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 1+ year(s) 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 2+ years of experience in business analytics, data science, software development, data modeling, or data engineering
OR equivalent experience
Ability to meet Microsoft, customer, and/or government security screening requirements may be required for this role. These requirements include, but are not limited to, the following specialized security screenings: Microsoft Cloud Background Check — this position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Nice to have
Experience designing and building production data solutions including ETL/data pipelines, backend services, or BI/reporting systems
Experience with PySpark, SQL, and Python, including data modeling, transformation, and pipeline development
Experience building or supporting REST APIs or data services, including schema design, versioning, and operations
Experience delivering Power BI or semantic modeling solutions, including DAX, Power Query (M), or curated datasets
Experience designing analytics or reporting with attention to performance, usability, and stakeholder consumption
Experience with data governance, data sharing, and access control (RBAC), including lineage, data quality, or compliance practices
Familiarity with data mesh, data products, or Data-as-a-Service concepts
Experience with Microsoft Azure or modern data platforms, including a combination of: Azure Data Factory, App Service, Functions, AKS, API Management, Microsoft Fabric (OneLake, Direct Lake), Synapse, Databricks, Azure SQL, or Cosmos DB
Experience with API standards and integration, including OpenAPI, Swagger, gRPC, GraphQL, or Microsoft Entra ID (Azure Active Directory)
Familiarity working in enterprise-scale data environments with diverse data sources
Experience contributing to data platforms, reporting hubs, or insights portals
Knowledge of privacy, security, or compliance practices, and interest in AI-ready data platforms (e.g., Copilot or agentic consumption patterns)