Principal Full Stack Engineer -Analytics Platform

Microsoft • Redmond, WA

1d • Hybrid

About The Position

Titan is Microsoft’s self-serve analytics platform, powering millions of queries monthly on trillions of rows of data across Bing, MSN, Edge, Windows, Copilot, and more. Titan democratizes data by putting trusted insights at everyone’s fingertips, cutting time to decision from days to seconds. From dashboards and advanced analytics to AI assisted experiences, Titan is the backbone of data informed innovation at Microsoft AI. We are looking for a Principal Full Stack Engineer to lead the next wave of analytics experiences. You will own end to end solutions, from rich interactive user interfaces to high performance analytical services with large language model integration, built on diverse big data infrastructure. In a fast paced, collaborative environment, you will architect systems that blend Microsoft and open source technologies, partnering with product, data engineering, and data science leaders to deliver tools used daily by thousands of internal teams shaping products for over one billion users worldwide. 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. Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Requirements

• Bachelor’s degree in computer science or related technical field AND 6+ years of engineering experience designing and operating production-scale systems with strong UX focus, with coding in languages including, but not limited to, Python, C++, C#, Java, or JavaScript OR equivalent experience

Nice To Haves

• Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, Python, C++, C#, Java, JavaScript OR Bachelor's Degree in Computer Science or related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, Python, C++, C#, Java, JavaScript OR equivalent experience.
• Front-end expertise: React, TypeScript, state management, performance, accessibility, data visualization (ECharts, Vega Lite, D3)
• Back-end experience: Node.js, Python, REST, GraphQL, microservices, asynchronous messaging, caching
• Strong SQL optimization and familiarity with columnar formats (Parquet, Delta, Iceberg)
• Cloud experience: Azure, CI/CD, containers, Kubernetes, infrastructure as code
• Security and reliability: OAuth, OpenID Connect, Azure AD, RBAC/ABAC, auditing, lineage, SLO ownership, incident response
• Apache Superset customization (plug-ins, embedding, dashboard performance, security integration)
• Experience with Databricks, Spark, ClickHouse, StarRocks, Cosmos DB, lakehouse/HDFS patterns
• Knowledge of experimentation frameworks, semantic layers, data catalogs, lineage, Microsoft Purview
• AI-assisted analytics: natural language SQL/KQL, automated insights
• Observability practices: OpenTelemetry, Prometheus, Grafana, Azure Monitor
• Statistical methods for product analytics

Responsibilities

• Architect and deliver intuitive analytics workflows for all skill levels: no code slice and dice, guided analysis, SQL, notebooks, and interactive app frameworks (e.g., Streamlit or Dash like).
• Advance security and governance with role based and attribute based access control, row and column level security, auditing, lineage, and cost controls; standardize metrics and the semantic layer across APIs, notebooks, and experiments.
• Drive performance and reliability by meeting latency and Service Level Objective (SLO) targets; apply caching, pushdown, and incremental compute; build robust observability with tracing, metrics, and logs.
• Mentor and empower globally distributed teams; collaborate across product, design, data engineering, privacy, and security; foster inclusive engineering practices.
• Infuse AI into analytics: natural language queries, automated insights, anomaly detection, and narrative summaries with clear governance guardrails.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees