Staff Technical Program Manager, Data Engineering
Pinterest is hiring a Staff Technical Program Manager, Data Engineering for a remote role open to applicants in United States. Level rates it ; you can apply on Pinterest.
Level's read on this job
- Level rates this data engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting lists this role as remote.
- Tools and skills the posting cites include Kafka, Flink and Iceberg.
- Level classifies it as a senior role.
- Level lists 169 other open roles at Pinterest.
AI in this role
Owns the strategy and execution of multi-year data platform modernization programs supporting machine learning pipelines at Pinterest.
About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
Pinterest's Data Engineering organization builds and operates the data platforms that power every Pinterest product — the batch and streaming pipelines that produce training data for our ML models, the storage and table formats that back our data lake, the workflow orchestration that runs it all, and the analytics platforms that fuel experimentation and decision-making. We're in the middle of a multi-year modernization effort: moving to streaming-first ingestion (CDC, Kafka, Flink), open table formats (Iceberg), a consolidated workflow platform, and retiring legacy footprints along the way. We work closely with ML, product, and analytics teams to make Pinterest's data platforms faster, more reliable, and more cost-efficient.
What You'll Do
- Own the strategy and execution of a multi-year portfolio of data platform modernization programs — spanning ingestion (CDC/Kafka/Flink), table format migrations (Hive to Iceberg), workflow consolidation, and legacy system deprecation — in partnership with engineering leaders across Data Engineering.
- Lead migrations across multiple orgs involving many producer and consumer teams: anticipate technical failure points early, resolve core technical uncertainties with engineering, and settle cross-org priority conflicts.
- Define the portfolio's metrics, governance, and reporting mechanisms so engineering, Platforms leadership, and Finance have a clear, current view of progress, validated savings, risk, and decisions.
- Own a large data infrastructure efficiency portfolio end to end, from savings strategy and forecasting to validation with team-level DRIs, Finance, and InfraGov.
- Influence senior leadership (up to VP/e-staff) with clear recommendations on technical tradeoffs, investment, and sequencing, and drive consensus across orgs.
- Mentor TPMs and engineering DRIs, and create best practices, tools, and methodologies that scale program management across the Platforms organization.
- 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.
What We're Looking For
- 8+ years of TPM experience leading complex, cross-functional technical programs, including strategic, multi-org programs or portfolios within large-scale data platforms, streaming systems, or data infrastructure modernization.
- Advanced understanding of large-scale data platforms — batch/streaming pipelines, table formats, storage layers, workflow orchestrators — and the ability to anticipate technical risk and influence architectural and roadmap decisions.
- A track record of defining program metrics and targets, building forecasting and savings models, and using data to drive investment decisions.
- A track record of influencing senior engineering and business leadership in high-visibility settings, driving consensus, and delivering difficult messages when needed.
- Comfort leading through ambiguity across all levels of leadership, making high-quality decisions with incomplete information.
- A track record of mentoring TPMs or engineers and building mechanisms that others adopt.
- Experience with streaming systems (Kafka, Flink), open table formats (Iceberg), or large-scale storage migrations is strongly preferred.
- 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.
Join us and help shape the foundation of Pinterest's data platform!
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
In-Office Requirement Statement:
- 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.
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At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
US based applicants only$123,684—$254,644 USDOur Commitment to Inclusion:
Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support. By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire.How we rate this
Staff Technical Program Manager, Data Engineering at Pinterest rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $149k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where stream processing was part of your work. What did you do?
- Tell me about a project where pipeline modernization was part of your work. What did you do?
- What's a project where you used Kafka hands-on?
- Walk me through how you've used Flink in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Data Engineering, Stream Processing, Pipeline Modernization, Kafka, and Flink. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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