Principal Data Engineering Architect

Microsoft • Redmond, WA

5d

About The Position

Microsoft’s Marketing Data Engineering Team transforms signals across web, campaigns, content, seller and partner interactions, and sales outcomes into trusted data products. The team helps marketers improve multi-channel customer engagement and learn through evidence, using 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 role shapes team strategy across data architecture, modeling, solution design, and data products, and provides technical direction for major capabilities. The architect works across partner engineering teams, enabling domain teams through shared standards, and collaborates with marketers, marketing technologists, analysts, and data scientists to connect customer and business needs to reusable capabilities.

The role enables Microsoft’s 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. It combines hands-on technical leadership with business acumen, autonomy, collaboration, 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.
• Proficiency in SQL and a programming language.
• Demonstrated expertise in distributed and big-data processing, streaming and batch systems, logical and physical data modeling, semantic abstraction, and schema evolution.
• 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.
• 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 so analysts, applications, and AI consumers can use data consistently.
• Design distributed processing and storage using streaming, batch, or combined patterns.
• Apply immutable event data and flexible schema evolution to protect downstream products.
• 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 that preserve domain ownership.
• Embed security, privacy, and quality by design, including metadata, lineage, classification, policy-aware access, and retention.
• Establish monitoring and engineering practices that make federated products trustworthy, supportable, and cost-conscious throughout their lifecycle.
• Advance AI automation and governed code generation for transformations, tests, documentation, and self-service data extension.
• Use bounded AI 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.

Benefits

• Certain roles may be eligible for benefits and other compensation; additional benefits and pay information is available through the Microsoft careers website.

What This Job Offers

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