Data Architect - Partner Engineering Platform (PEP) Reporting

Microsoft • Redmond, WA

1d

About The Position

Overview
The Partner Engineering Platform (PEP) Reporting team within WECE powers high scale telemetry insights that help Microsoft’s OEM and silicon partners improve device reliability and elevate the Windows customer experience worldwide.
As a Data Architect, you will lead the design and evolution of largescale distributed data platforms that ingest and processes Windows OEM telemetry at a multibillion record scale. You define architecture patterns, shape end-to-end data flows, and ensure the platform meets strict availability, latency, governance, and performance requirements.
You will partner with TPMs, engineering leads, and data science teams to set technical directions and deliver next generation reporting and AI powered experiences that support mission critical insights across the Windows ecosystem.
This role is built for architects who excel at driving clarity, establishing scalable platform patterns, and guiding teams toward long term, resilient data architecture solutions.

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 designing and architecting distributed data systems or analytics platforms.
• Deep experience with Microsoft data technologies—including: Microsoft Kusto (ADX) clusters and advanced KQL (query optimization, partitioning, ingestion mapping, materialized views, update policies).
• Azure Data Lake / Lakehouse / Data Stores (Delta/Parquet, hierarchical partitioning, metadata and schema management).
• Demonstrated success tuning and optimizing large-scale analytical systems for performance, reliability, and availability.
• Strong expertise in designing data models, distributed query patterns, and ingestion strategies for datasets larger than 5 billion records.
• Experience architecting real-time analytics solutions, including latency-aware data structures enabling sub-second slicing/aggregation for dashboards or AI Agents.
• Proficiency with data security, privacy, governance, and compliance best practices for enterprise data systems.
• Ability to drive architectural decisions across organizations and influence engineering teams toward scalable, long-term data strategies.
• Experience with Azure Cosmos DB (Core/SQL, API design, partitioning, RU optimization, change feed).
• Experience with COSMOS-to-Kusto patterns, parquet compaction strategies, or high-fidelity telemetry pipelines supporting reliability and health signals.
• Familiarity with AI/ML operationalization, vectorized data flows, or embedding augmented analytics pipelines.
• Experience leading large data architecture initiatives in cloud-scale environments.
• Excellent communication, executive facing storytelling, and cross functional collaboration skills especially in data-driven engineering organizations like WECE, Data Sciences, DSQ, WATSON, and Windows Fundamentals Reliability.

Responsibilities

• Architect, design, and maintain distributed data platforms supporting OEM telemetry, reliability analytics, compliance signals, and AI-driven data products.
• Establish end-to-end data architecture patterns for ingestion, curation, enrichment, aggregation, and publication across Microsoft Kusto clusters, Azure Cosmos DB, Azure Data Lake/Lakehouse, and COSMOS streaming and parquet-based pipelines.
• Own schema modeling, partitioning strategy, indexing, caching, and performance tuning for largescale structured, semi structured, and timeseries datasets.
• Develop architectural blueprints enabling real-time or near real-time slicing, filtering, and aggregation across billions of records to support AI Agents, partner facing dashboards, and internal engineering workflows.
• Drive availability, resiliency, cost optimization, and governance across high-scale data workloads, ensuring SLAs and SLOs for mission critical reporting pipelines.
• Partner with engineering teams to establish best practices for data quality, observability, lineage, security, and access patterns, including RBAC and compliant handling of sensitive telemetry.
• Guide engineers in building scalable data ingestion and transformation pipelines using Microsoft data plane technologies, including KQL-based ETL, parquet transformations, and high throughput telemetry streams.
• Collaborate closely with PEP TPMs on roadmap definition, platform migrations, and data driven initiative planning.

What This Job Offers

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