Manager, Data Engineering

Thumbtack helps millions of people confidently care for their homes.

Thumbtack is the one app you need to take care of and improve your home — from personalized guidance to AI tools and a best-in-class hiring experience. Every day in every county of the U.S., people turn to Thumbtack to complete urgent repairs, seasonal maintenance and bigger improvements. We help homeowners know which projects to do, when to do them and who to hire from our growing community of 300,000 local service businesses. If making an impact inspires you, join us. Imagine what we’ll build together.

About the Data Engineering Team

Thumbtack's Data organization is responsible for the foundations of our marketplace data: the event taxonomy used across product surfaces, the core entity models for requests, projects, pros, and customers, and the financial models that support company reporting. Nearly every team at Thumbtack is downstream of our work.

Data Engineering is organized as domain-aligned teams, each embedded with the parts of the business it serves, working alongside a platform team that owns the systems underneath. Data modeling at Thumbtack is a function of how well you understand the domain you're modeling, so we put engineers close to it and hold them to a high bar on correctness, testing, and the durability of what they ship.

The challenge

This team works at the intersection of financial data governance and rapid product iteration. Thumbtack’s revenue models must be auditable, reconcilable, and resilient to upstream changes. At the same time, the teams responsible for Pro acquisition, activation, and partnerships are continually evolving the products, often affecting the same models Finance relies on.

The team has already introduced anomaly detection into its core pipelines to identify upstream definition changes before they affect revenue reporting, but the next step is to develop predictive capabilities that show how proposed product and data-model changes could affect financial results before those changes are released.

The stack includes BigQuery, dbt, Airflow, and MetricFlow. dbt testing and CI are already established, with significant opportunities to expand automation. The team also owns the governance tooling used to protect core pipelines and maintain trusted data across the company.

Thumbtack is also rebuilding the platforms that support sales, support, and trust & safety around API-first systems and agentic workflows. A separate, funded team owns the platform work; this team will be responsible for helping architect the resulting data beginning next year.

The team this role will lead is organized into two subteams: one partners closely with Finance, while the other is embedded with Supply Acquisition and Business Platforms. Several engineers will be joining at roughly the same time as you. Each subteam owns its roadmap, giving you a direct role in setting priorities and shaping how the team operates.

What you’ll do

Deliver well-modeled, durable datasets for requests, projects, pros, and customers that the rest of the company builds on without asking who owns them.

Partner with Finance so revenue models reconcile, hold their definitions under upstream change, and are auditable.

Partner with the Supply Acquisition and Business Platforms teams on their roadmaps, and turn their priorities into yours without waiting to be handed tickets.

Raise the reliability floor on the core pipelines: dbt tests, CI, anomaly detection, and clear contracts so a definition change three hops upstream doesn't quietly move a reported number.

Hire and grow mid-level and senior data engineers, and develop TLs who can own a domain end-to-end.

Set the engineering standards for a team that's still forming, including review, testing, and how the team decides what not to build.

Lead as a technical manager. You'll make and defend modeling and architecture decisions, not just route them.

In order to be successful, you must bring

2+ years managing engineers, or experience as a tech lead ready to step into first-line management.

6+ years building data or software systems in production.

Depth in SQL and dimensional and event modeling, and comfort in Python. You'll be in code reviews, in the DAG when something breaks, and in modeling design discussions.

Experience owning datasets that other teams depend on, with the testing, contracts, and versioning discipline that requires.