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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Technical Program Manager, Data Engineering - **Company:** Pinterest - **Location:** San Francisco, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $123,684.0 - $254,644.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Big Data, Information Engineering, Data Infrastructure, Apache Hive, Workflow Management Systems, Data Processing, Information Technology, Apache Flink, Apache Kafka, Data Management, Stream Processing - **Published:** September 24, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18418320?backUrl=%2Fcareer%2F18418320%2FSr-Technical-Program-Manager-Data-Engineering-California-San-Francisco ## About the Role * 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. * 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. * 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. ## Description * 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., * We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role. * 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. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Building the platform for providing ML predictions based on real-time player activity](https://www.wearedevelopers.com/videos/944-building-the-platform-for-providing-ml-predictions-based-on-real-time-player-activity) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Python-Based Data Streaming Pipelines Within Minutes](https://www.wearedevelopers.com/videos/1233-python-based-data-streaming-pipelines-within-minutes) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)