Staff Product Manager, Data Platform

The Trade Desk•San Francisco, CA

9h•$201,400 - $251,800

About The Position

The Trade Desk is seeking a Staff Product Manager to shape the data platform supporting its global digital advertising business. This senior individual contributor will lead product vision, strategy, and priorities for the platform, connecting business direction to capabilities that help teams across the company build and deliver products more effectively. The role focuses on ensuring large volumes of data are collected, processed, and made available accurately, reliably, securely, and efficiently, while evolving the platform to support AI-native products and agent-driven workflows. The position works closely with engineering and teams that produce and consume data, as well as product, data science, analytics, business, governance, and security stakeholders. The Product Manager will develop a multi-year strategy and actionable roadmap, build alignment across organizational leaders, and guide platform investments from planning through delivery, adoption, and measurement. The role emphasizes shared capabilities, developer experience, trusted and discoverable data, and delivering useful increments while balancing performance, reliability, flexibility, cost, and time to value.

Requirements

At least 6 years of product management experience, including substantial experience building data platforms, infrastructure, or technical products at scale.
Experience leading initiatives across multiple teams from strategy through delivery and adoption.
Exceptional communication and organizational influence, including the ability to explain complex technical ideas, write strategy and requirements documents, communicate the business value of foundational work, and align directors, VPs, and technical leaders.
Ability to navigate competing priorities, challenge assumptions constructively, and drive decisions without formal authority.
Experience setting platform vision and strategy and translating needs across products or business areas into a coherent roadmap for shared capabilities.
Ability to connect near-term decisions with long-term direction and distinguish durable needs from uncertain possibilities.
Deep technical fluency in data systems, including ingestion, batch and streaming processing, storage and query systems, data modeling, APIs, schema evolution, and downstream dependencies.
Ability to reason about data-system tradeoffs involving throughput, latency, reliability, scalability, and cost.
Strong SQL skills and comfort exploring datasets, investigating data-quality issues, and using evidence to test assumptions.
Understanding of how data definitions, granularity, lineage, and freshness affect products and decisions.
Product mindset for internal platforms, including treating platform users as customers and investing in developer experience, adoption, and usability.
Strong judgment and independent execution, including structuring ambiguous problems, prioritizing competing needs, delivering useful increments with engineering, taking responsibility for results, and improving products after launch.

Nice To Haves

Background in software engineering, data engineering, analytics engineering, or a similarly technical discipline.
Experience with digital advertising, programmatic platforms, or other businesses where high-volume data systems are central to the product.
Experience preparing data platforms for AI and agent-driven workflows, including making data discoverable, interpretable, and securely accessible to models and agents.
Experience leading platform migrations, consolidating fragmented data systems, or evaluating whether to build, buy, or extend foundational capabilities.

Responsibilities

Set the data platform vision and strategy, translating it into a multi-year strategy and actionable roadmap with clear priorities, tradeoffs, and measures of success.
Build relationships with product, engineering, data science, and business leaders to understand future plans, identify dependent data capabilities and gaps, and communicate future platform needs.
Understand the workflows and constraints of engineers, data scientists, analysts, and product teams, and prioritize shared platform capabilities that address common needs.
Partner with engineering leaders on data ingestion, processing, storage, discovery, and serving; write product vision and requirements documents and make informed technical and business tradeoffs.
Champion platform investments, explain their value to technical and business audiences, develop investment cases, and align stakeholders around priorities and dependencies.
Partner with engineering, governance, and security teams to establish expectations for data quality, freshness, discoverability, access, and reliability.
Advocate for clear interfaces, documentation, and self-service workflows that improve platform adoption and usability.
Break long-term investments into useful increments and coordinate dependencies, migrations, and adoption across teams.
Balance new capabilities with improvements to existing foundations and adapt the roadmap as business needs and technical understanding evolve.
Measure platform impact using outcomes such as faster delivery, shorter onboarding, greater reuse, stronger reliability, and better cost efficiency; combine usage data with user feedback and address underperforming investments.

Benefits

Comprehensive medical, dental, and vision healthcare, with premiums paid in full for employees and dependents.
401(k) retirement plan with company match.
Short- and long-term disability coverage.
Basic life insurance.
Well-being benefits.
Reimbursement for certain tuition expenses.
Parental leave.
Sick time of 1 hour per 30 hours worked.
Vacation time for full-time employees: up to 120 hours through the first year and 160 hours thereafter.
Approximately 13 paid holidays per year.
Opportunity to purchase company stock at a discount through the Employee Stock Purchase Plan.
Employees may be eligible for stock-based compensation grants, awarded based on employee and company performance.
Other compensation may include variable compensation-based incentives and commissions, depending on the role.