Sr Principal Data Engineer

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Salary $ On request
Location San Francisco, CA
Work Type On-site
Employment Type Full Time
Posted On May 7, 2026
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Job Description

Why UKG At UKG, the work you do matters. The code you ship, the decisions you make, and the care you show a customer all add up to real impact. Today, tens of millions of workers start and end their days with our workforce operating platform. Helping people get paid, grow in their careers, and shape the future of their industries. That’s what we do. We never stop learning. We never stop challenging the norm. We push for better, and we celebrate the wins along the way. Here, you’ll get flexibility that’s real, benefits you can count on, and a team that succeeds together. Because at UKG, your work matters–and so do you. About the Role As a Senior Principal Data Engineer within the Enterprise Data & Analytics Office, you will lead the design, evolution, and operational excellence of Nexus, UKG’s unified, GCP-based data platform, enabling analytics, AI, and enterprise decision-making at scale. You will translate architectural vision into reliable, scalable, cost-efficient data systems, lead platform modernization efforts, and set the engineering bar for data ingestion, transformation, and operational analytics across UKG. Key Responsibilities: Enterprise Data Engineering Leadership • Drive the implementation of standardized medallion architecture (Bronze-Silver-Gold) across all domains. • Establish and enforce engineering patterns for batch, streaming, CDC, and event-driven pipelines. • Drive design patterns for Fact and Dimension modeling, data mesh, and change data capture (CDC). Platform & Pipeline Excellence • Design and evolve scalable data pipelines using GCP-native services (BigQuery, GCS, Composer, Pub/Sub, Dataflow) and Databricks (Delta Lake, DLT). • Ensure platform reliability, performance, and scalability for petabyte-scale analytics workloads. • Lead engineering decisions around partitioning, clustering, query optimization, and cost controls (FinOps). • Own observability standards (freshness, SLAs, error handling, monitoring). Engineering Standa…

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