Build the checks that make a certified metric trustworthy: reconciliation against sources and existing reports, data quality and freshness monitoring, and alerts that catch problems before they reach a dashboard or an agent.
Make Xbox data ready for AI agents. Provide the metadata, lineage, documentation and query patterns agents need to find the right metric, and help build the evaluation sets that measure whether agents answer correctly.
Bring data science judgment to the model: use telemetry analysis to choose sound definitions, design metrics that work in A/B experiment scorecards, and explain unexpected metric movements.
Set the standards for publishing certified data, including ownership, lineage, access controls and catalog documentation, and retire duplicate or uncertified assets as their replacements are certified.
Lead through influence across the XBOX data organization: review designs, mentor engineers and data scientists, and use AI tools to speed up your own and the team’s work.
Qualifications
Required Qualifications
Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR equivalent experience.
Preferred Qualifications
8+ years of experience building and operating production data pipelines and data models, using SQL and Python on Spark-based platforms such as Databricks.
Experience designing a semantic or metric layer (e.g., Databricks Unity Catalog metric views or Power BI semantic models), and dimensional data models.
3+ years of hands-on data science or analytics experience, such as defining product metrics, analyzing large-scale telemetry and applying statistical methods.
Experience designing metrics for online experimentation (A/B testing), including metric sensitivity, variance and guardrail metrics.
Experience validating data and metrics at scale, including reconciliation against source systems and the error tradeoffs of approximate distinct counts.
Experience making data usable by AI agents or LLM applications, such as text-to-SQL, retrieval over catalogs and documentation, Model Context Protocol (MCP) tools, or evaluation sets that measure answer accuracy.
Experience applying data governance in a large organization, including ownership, lineage, access controls and privacy requirements.
Experience using AI tools, such as GitHub Copilot, in data engineering and analytics work.
Experience with gaming, subscription or other consumer products.
#GamingJobs
Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
- Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
- https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
