Sr. Technical Program Manager, Data Engineering

Pinterest is a platform that helps people discover creative ideas and plan meaningful experiences. The company is seeking a Senior Technical Program Manager to lead data platform modernization programs, coordinate cross-functional migrations, track infrastructure efficiency, and communicate progress, risks, and technical tradeoffs to stakeholders. The role also focuses on using GenAI and data-driven tools to improve program execution while meeting AI governance and safety requirements.

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 surface risks, decision/trade-offs, and escalation paths
• 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

Requirements:

• 5+ years of TPM experience leading complex, cross-functional technical programs, ideally within large-scale data platforms, streaming systems, or data infrastructure modernization efforts
• Solid understanding of the principles behind large-scale data platforms — batch/streaming pipelines, table formats, storage layers, workflow orchestrators — and the tradeoffs involved in modernizing them
• Excellent analytical and problem-solving skills, with experience building dashboards, interpreting data, and using insights to drive decisions and validate savings
• Strong collaboration and communication skills, with a track record of partnering with senior engineering and business stakeholders in high-visibility settings
• Comfort with ambiguity and shifting priorities across a fast-moving, multi-workstream roadmap
• Workflow design, AI fluency, data & insights orientation: experience turning repeatable program work into durable, low-toil mechanisms and improving decision-making by using GenAI (e.g., strong prompting, vibe coding lightweight scripts/tools, dashboards, data analysis and leveraging agents where appropriate)
• Safety-by-design AI fluency: experience operating within AI governance expectations (risk assessment, data handling, model/output validation, auditability/traceability) and proactively identifying where AI use is not appropriate or requires additional controls
• Bachelor's degree in Computer Science, Engineering, a related field or equivalent experience
• This role will need to be in the office for in-person collaboration 1–2 times every 6 months and therefore can be situated anywhere in the country
• US based applicants only
• Experience with data platforms, streaming systems (Kafka, Flink), or open table formats (Iceberg) is a plus; willingness to learn and grow across domains is essential