Senior Data Engineer

Microsoft•Redmond, WA

About The Position

The Windows Ecosystem & Commercial Engagement (WECE) – Quality, Reliability, and Telemetry (QRT) team is responsible for ensuring Windows ships safely, reliably, and at scale across the full ecosystem—including Microsoft‑owned devices, OEMs, silicon partners, and third‑party hardware and software configurations. As a Senior Data Engineer on the QRT team, you will own and evolve the internal data platforms that power Windows quality, selfhost readiness, and ecosystem decision‑making. This role is focused on building durable, governed data pipelines and analytical foundations across Asimov telemetry, Cosmos/Spark, Windows Census, and Power BI, enabling engineering teams and leadership to act on trusted signal. This is not a reporting‑only role. You will be responsible for end‑to‑end data systems—from ingestion and modeling to reliability, governance, and operational excellence. What You’ll Work On You will design, build, and operate internal Microsoft data platforms that support Windows engineering and ecosystem readiness, including: Telemetry pipelines built on Asimov and Cosmos/Spark. Authoritative datasets derived from Windows Census and related device telemetry. Curated, governed analytical models consumed via Power BI. Data systems that enable early selfhost signal, partner readiness tracking, and quality risk detection. Your work will directly influence how quickly Windows teams can identify issues, validate updates, and ship with confidence—before retail impact. 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.

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.

Nice To Haves

5+ years of experience building and operating production data systems.
Solid experience with SQL, Kusto, and data modeling (fact/dimension modeling, device‑centric analytics, semantic layers).
Proficiency in one or more data‑engineering languages (e.g., Python, Scala, Java, C#).
Experience operating data pipelines at scale with reliability and governance requirements.
Demonstrated ability to debug production issues and drive root cause to closure.
Solid collaboration skills across engineering, product, and partner teams.
Hands‑on experience with Asimov telemetry, Cosmos/Spark, or large‑scale internal telemetry systems.
Experience working with Windows Census or device‑level telemetry.
Building Power BI semantic models and supporting executive‑level reporting.
Experience with Azure‑based data platforms (ADLS, Databricks, Fabric, Synapse).
Familiarity with privacy‑sensitive telemetry and consent‑driven data models.
Experience supporting selfhost, validation, or ecosystem readiness programs.

Responsibilities

Architect, implement, and operate batch and streaming data pipelines ingesting telemetry from internal Windows systems.
Build and maintain authoritative datasets using sources such as Windows Census, device telemetry, and selfhost participation data.
Design and enforce data contracts, schemas, and semantic models that are stable, documented, and easy to consume.
Develop curated analytical layers and semantic models that power Power BI dashboards for engineering and leadership.
Own data quality and reliability: validation, deduplication, anomaly detection, backfills, and reprocessing.
Integrate privacy, security, and governance requirements into all data pipelines and access patterns.
Optimize for scale and cost, balancing compute, storage, retention, and performance.
Build and operate observability for data systems (metrics, logging, alerts, runbooks, incident response).
Partner closely with: QRT engineers Internal Windows Engineering teams WECE selfhost and partner programs Privacy, security, and compliance stakeholders
Mentor early in career engineers and raise the bar for engineering rigor, ownership, and operational maturity.