Principal Data Engineering Architect

Microsoft • Redmond, WA

6d • $142,800 - $304,200

About The Position

Microsoft’s Marketing Data Engineering Team transforms signals from web, campaigns, content, seller and partner interactions, and sales outcomes into trusted data products that help marketers improve customer engagement and learn through evidence. The team uses AI-native self-service to make trusted data easier to find and use.

The Principal Data Engineering Architect leads the architecture and hands-on development of petabyte-scale systems processing billions of events per day. This individual contributor shapes team strategy across data architecture, modeling, solution design and data products, and provides technical direction for major capabilities while influencing partner engineering teams through shared standards.

The role connects marketing and customer needs to reusable capabilities, working with marketers, marketing technologists, analysts and data scientists. It enables the Marketing organization to turn raw data into trusted, scalable, AI-ready data products that support campaign performance measurement, customer intelligence, audience engagement, revenue growth and executive decision-making through the Microsoft Fabric ecosystem. The position combines autonomous, hands-on technical leadership with business judgment, cross-functional collaboration, mentoring and accountability for operational reliability and measurable product outcomes.

Requirements

• Master's degree in Computer Science, Math, Software Engineering, Computer Engineering or a related field and 4+ years of experience in business analytics, data science, software development, data modeling or data engineering; or bachelor's degree in one of these fields and 6+ years of relevant experience; or equivalent experience.
• Demonstrated expertise in distributed and big-data processing, streaming and batch systems, logical and physical data modeling, semantic abstraction and schema evolution.
• Proficiency in SQL and a programming language.
• Proficient business acumen and product judgment, including the ability to understand business users, translate ambiguous needs into reusable data capabilities, and connect engineering decisions to customer and business outcomes.
• Demonstrated cross-functional technical leadership, mentoring and influence through partnership.
• Clear written, verbal and presentation communication for technical and business audiences, and sound judgment informed by quantitative and qualitative evidence in fast-moving, ambiguous environments.

Nice To Haves

• Master's degree in Computer Science, Math, Software Engineering, Computer Engineering or a related field and 8+ years of experience in business analytics, data science, software development, data modeling or data engineering; or bachelor's degree in one of these fields and 12+ years of relevant experience; or equivalent experience.
• 3+ years of experience with data governance, data compliance and/or data security.
• 8+ years of experience across the software development lifecycle, including 2+ years in a technical lead role designing and delivering large-scale data platforms.
• Experience with marketing, digital media or web analytics, customer journey measurement, and data products supporting analytics, data science and activation.
• Experience building federated self-service platforms or governed AI-assisted engineering and discovery tools, with evidence of improved adoption, delivery efficiency or operational quality.

Responsibilities

• Partner with product managers and business users to define problems, connect requests to customer journeys and business outcomes, and prioritize reusable capabilities; use feedback, adoption, reuse and quality measures to guide product decisions and team data strategy.
• Lead solution design and production implementation of major data capabilities; build hands-on prototypes, contribute production code, review code, models and designs, and remain accountable for operational reliability and measurable product outcomes.
• Develop logical, physical and semantic models for foundational marketing domains; productize engagement signals with clear business definitions, metric logic, contracts and ownership.
• Design distributed processing and storage using streaming, batch or combined patterns; apply immutable event data and flexible schema evolution; make explicit tradeoffs among latency, accuracy, reliability, cost and maintainability.
• Influence engineering and user-facing tools for governed self-service ingestion, publishing and extension of platform data; improve discovery, access and user experience through interoperable templates, interfaces and semantic abstractions while preserving domain ownership.
• Embed security, privacy and quality by design, including metadata, lineage, classification, policy-aware access and retention; establish monitoring and engineering practices for trustworthy, supportable and cost-conscious federated products.
• Advance AI automation and governed code generation for transformations, tests, documentation and self-service data extension; use bounded assistance for operational detection and recommendations with rigorous validation, approved remediation and human judgment for consequential changes; measure delivery and operational improvements.
• Listen, simplify, iterate quickly and make sound decisions in a large, complex data environment; mentor and coach engineers, strengthen reviews and standards, and align partner teams through technical credibility and collaboration.
• Embody Microsoft's culture and values.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal