Data Engineer II

Data Engineer II

United States, Washington, Redmond

Job description

Company and benefits

Job number

Date posted

Work site

3 days / week in-office

Travel

Less than 25%

Profession

Software Engineering

Discipline

Data Engineering

Role type

Individual Contributor

Employment type

Full-Time

Overview

The Supportability & Customer-Centric Engagement and Engineering Direct (SUCCEED) Team, part of the broader Windows Servicing Delivery (WSD) organization, is looking for a Data Engineer II to help build the data foundation for engineering, customer supportability, customer escalation, and operational intelligence scenarios. This role will design, build, and maintain reliable data pipelines, telemetry datasets, measurement models, and dashboards that help engineering, product management, support, and leadership teams make timely, data-driven decisions.

This person will demonstrate solid data engineering fundamentals, have experience working with telemetry and operational datasets, and the ability to turn ambiguous business questions into scalable, trustworthy data products.

At Microsoft, our mission—to empower every person and every organization on the planet to achieve more—guides how we partner with customers to deliver trusted, impactful solutions. With a growth mindset culture, we innovate responsibly and measure success by shared progress—people, teams, and customers. Join us to do meaningful work that changes the world and helps shape what’s next for everyone.

Responsibilities

• Build and maintain data pipelines, transformations, semantic models, and curated datasets across engineering and operational data sources.
• Partner with product management, engineering teams, support teams, and leadership stakeholders to define metrics, key business measures, and data quality expectations.
• Develop telemetry validation, data freshness, completeness, and reliability checks.
• Create and maintain dashboards, scorecards, and operational reporting, including Microsoft reporting tools or equivalent reporting experiences.
• Integrate data from systems such as Azure DevOps, telemetry platforms, support and escalation systems, release-readiness sources, and business reporting tools.
• Automate manual reporting and intake workflows where possible.
• Improve discoverability, governance, ownership, and documentation of critical datasets.
• Support release readiness, customer health, feature adoption, supportability, and escalation analytics.
• Investigate data issues, root-cause reporting anomalies, and drive