Senior Data Engineer

Thumbtack's Data Engineering org is split into 3 groups: Core Data Engineering, Data Platform and Embedded Data Engineering. This role is on the Embedded Data Engineering team, which breaks down into multiple business units that data engineers are embedded into. This role would be on the commercial operations side of the house and will work closely with engineers, analysts, data scientists and machine learning engineers to help design and curate data sets originating from internal and third-party sources to meet current and future needs.

Responsibilities

Collaboratively refine and evangelize a comprehensive framework for integrating data-thinking into the software development lifecycle for product teams.; Design, architect, and maintain core operations datasets, data marts, and feature stores that support a blend of mature products and features with a rapidly evolving product line, in partnership with analytics, data science, and machine learning.; Integrate deeply with our cross functional partners to understand their data needs, and help design datasets with the same engineering rigor as any other software we design.; Drive data quality and best practices across different business areas.; Help build the next generation data products at Thumbtack, leveraging AI models for code generation and incorporating agents into our workflows.

Requirements

4+ years of experience designing and building data sets and warehouses.; Excellent ability to understand the needs of and collaborate with stakeholders in other functions, especially Analytics, and identify opportunities for process improvements across teams.; Expertise in SQL for analytics/reporting/business intelligence and also for building SQL- and Python-based transforms inside an ETL pipeline, or similar.; Experience designing, architecting, and maintaining a data warehouse and data marts that seamlessly stitches together data from production databases, clickstream data, and external APIs to serve multiple stakeholders.; Expertise building the above with a modern data stack based on a cloud-native data warehouse, in our case we use BigQuery, dbt, and Apache Airflow, but a similar stack is fine.; Experience using AI to generate design plans, code and documentation as well as applying AI-enabled workflows to accelerate development velocity and improve data engineering practices.; Strong sense of ownership and pride in your work, from ideation and requirements-gathering to project completion and maintenance.