Manager, Data Engineering

Thumbtack•San Francisco, CA

13d•Remote

About The Position

Thumbtack's Data Engineering Team is responsible for the foundational elements of the company's marketplace data, including the event taxonomy, core entity models (requests, projects, pros, customers), and financial models for company reporting. The team operates with domain-aligned groups embedded within business units, supported by a platform team. Data modeling is emphasized, requiring engineers to deeply understand the domains they model and maintain high standards for correctness, testing, and durability. This role specifically addresses the challenge of balancing financial data governance with rapid product iteration, ensuring revenue models are auditable, reconcilable, and resilient to upstream changes. The team is developing predictive capabilities to assess the impact of proposed changes on financial results before release, utilizing BigQuery, dbt, Airflow, and MetricFlow. The role involves leading a team organized into two subteams: one partnering with Finance, and the other embedded with Supply Acquisition and Business Platforms. The manager will play a direct role in setting priorities and shaping team operations.

Requirements

2+ years managing engineers, or experience as a tech lead ready for first-line management.
6+ years building data or software systems in production.
Depth in SQL and dimensional and event modeling.
Comfort in Python.
Experience owning datasets that other teams depend on, with the necessary testing, contracts, and versioning discipline.
Track record of translating ambiguous business questions into durable models and metric definitions.
Strong collaboration and written communication skills.
Commitment to building inclusive teams and team culture.

Nice To Haves

Experience with BigQuery, dbt, Airflow, and MetricFlow.
Experience with anomaly detection in data pipelines.
Experience with API-first systems and agentic workflows.

Responsibilities

Deliver well-modeled, durable datasets for requests, projects, pros, and customers.
Partner with Finance to ensure revenue models reconcile, maintain definitions under upstream change, and are auditable.
Partner with Supply Acquisition and Business Platforms teams on their roadmaps and translate their priorities into team actions.
Raise the reliability floor on core pipelines through dbt tests, CI, anomaly detection, and clear contracts.
Hire and grow mid-level and senior data engineers, and develop technical leads.
Set engineering standards for a forming team, including review processes, testing, and decision-making on what not to build.
Make and defend modeling and architecture decisions as a technical manager.