Sr. Technical Program Manager, Data Engineering

Responsibilities

• Lead a multi-quarter portfolio of data platform modernization programs — spanning ingestion (CDC/Kafka/Flink), table format migrations (Hive to Iceberg), workflow consolidation, and legacy system deprecation — partnering with engineering leads across the Data Engineering organization.
• Drive cross-team execution on migrations that involve many producer and consumer teams, managing timeline, dependency, and risk across service owners.
• Build and maintain program dashboards and reporting that give engineering and Platforms leadership a clear, current view of progress, validated savings, risk, and decisions.
• Own the reporting and tracking function for a large data infrastructure efficiency portfolio, coordinating with team-level DRIs and partner finance/InfraGov stakeholders.
• Communicate technical tradeoffs and program status clearly to both technical and non-technical audiences, from individual engineers to senior leadership.
• Use GenAI as the default operating model for EP PgM execution—producing AI-assisted first drafts of core program artifacts, modernizing high-toil workflows into AI-first mechanisms (e.g., intake triage, status synthesis, action/decision extraction, risk & dependency tracking), and synthesizing signals to proactively…
• Prototype solutions to augment decisions through data (e.g. dashboards, data analysis) or simplify processes (e.g. process and workflow helpers, or internal tools) using AI coding assistants (“vibe coding”).
• Follow Pinterest AI guidance for risk, governance, and safety-by-design: appropriately handle sensitive data, validate AI-generated outputs, document assumptions/limits, and ensure AI-assisted workflows meet applicable policy/compliance expectations before broad adoption.

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