Staff Software Engineer, Data Platform

About the Data Platform Team

Data is the lifeblood of modern companies, and for a two-sided digital marketplace like Thumbtack, even more so. The Data Platform team is a central team of software engineers who employees with various backgrounds can easily build pipelines, systems, and models, all while keeping Customer and Pro privacy in mind. You’ll work deeply with Data Scientists, Machine Learning Engineers, and other Software Engineers from across the company as customers, and collaborate closely with the Site Reliability and core service Engineering teams as partners.

Challenge

In 2024, Thumbtack is significantly investing in Data initiatives and the Engineering teams that support them, as a strategic growth area for the company. While there are interesting and difficult challenges across the entire focus area, this team is specifically poised to build the deep technological foundation to empower all others. It’s highly-leveraged, intricate and interesting work for the right type of engineer. We are the caretakers and creators of the foundational building blocks of the modern Thumbtack data system, and we need your help to build and deliver that.

Responsibilities

• Collaboratively refine and evangelize a comprehensive framework for integrating data-thinking into the software development lifecycle across Engineering
• Work with the Data Engineering and Machine Learning teams as stakeholders to identify gaps in our current capabilities, and help build and execute on a multi-year roadmap to close them
• Directly work with teams consisting of product engineers, analysts, data scientists, machine learning engineers throughout the company to understand their data needs, and make recommendations both how to build to their needs, but also to build processes and knowledge bases to support them
• Drive data quality and best practices across the company
• Help build the next generation of marketing data products at Thumbtack, based on real-time data products on top of Apache Kafka

Must-Have Qualifications

If you don't think you meet all of the criteria below but still are interested in the job, please apply. Nobody checks every box, and we're looking for someone excited to join the team.

• 8+ years of experience in software engineering, at least 2 of which focused in the data domain
• Excellent ability to understand the needs of, and collaborate with, stakeholders in other functions, especially other Engineering teams
• Strong fluency in at least one major programming language and would be able to switch between multiple languages. Thumbtack’s main production stack is Go, however we tend to use Python with some Scala
• Experience designing, architecting, and maintaining data systems that serve deeply technical customers
• Strong sense of ownership and pride in your work, from ideation and requirements-gathering to project completion and maintenance

Nice-to-Have Qualifications

• Experience building ETL data pipelines in a modern programming language, like Python or Scala, ideally with Apache Airflow
• Understanding of database internals and query optimization
• Experience working with semi-structured or unstructured data in a data lake or similar
• Experience working in engineering at a two-sided marketplace or B2C technology company
• Experience mentoring and coaching data engineers and/or analysts

Thumbtack is a virtual-first company, meaning you can live and work from any one of our approved locations across the United States, Canada or the Philippines.* Learn more about our virtual-first working model here.

For candidates living in San Francisco / Bay Area, New York City, or Seattle metros, the expected salary range for the role is currently $202,000 - $248,000. Actual offered salaries will vary and will be based on various factors, such as calibrated job level, qualifications, skills, competencies, and proficiency for the role.

For candidates living in all other US locations, the expected salary range for this role is currently $172,000 - $210,000. Actual offered salaries will vary and will be based on various factors, such as calibrated job level, qualifications, skills, competencies, and proficiency for the role.