Data Engineer II

Shape the future of Surface by building the data backbone that powers insights, innovation, and customer delight. The Surface insights and intelligent experiences team drives strategic insights and innovation across Microsoft by transforming complex data into actionable intelligence and customer facing experiences. By connecting data, technology, and business priorities, the team ensures Microsoft stays ahead in delivering value at global scale.

As a Data Engineer II in the data services team, you will design and build scalable data pipelines, optimize data flows, and ensure the integrity and availability of mission-critical datasets. You’ll partner closely with data science, analytics, product, and engineering teams to transform data and raw telemetry into actionable insights that drive both product innovation and experiences that empower partners and customers.

This opportunity will allow you to:

• Accelerate your career growth by working on high-impact, global-scale data systems.
• Develop deep technical expertise in modern data platforms, cloud services, and big data technologies.
• Hone your problem-solving skills by tackling complex challenges in performance, reliability, and data quality.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

• Design, build, and operate batch and streaming data pipelines that ingest from diverse sources into cloud data platforms (e.g., ADLS Gen2/Microsoft Fabric, Synapse/Azure SQL/Cosmos DB), with strong SLAs and observability.
• Develop services and APIs that expose curated datasets and features to downstream applications and ML/analytics scenarios; contribute to backend components, testing, and performance tuning.
• Harden security and networking for data workloads (e.g., private endpoints, VNet/VPN integration, role‑based access, key management), partnering with security and networking teams.
• Automate and productize: apply DevOps/DataOps (GitHub/Azure DevOps, CI/CD, IaC such as Bicep/Terraform) to deliver reliable releases, repeatable environments, and cost‑efficient operations.
• Collaborate & document: write design docs, review code, and work cross‑functionally with PMs, data scientists, and stakeholders.