Key skills
Data system designSQLPythonCloud-native warehousesData quality best practicesData architectureCollaboration skillsScalability reasoningMentoringOwnershipMachine LearningAnalyticsSnowflakeBigQueryKafkaApache KafkaAirflowdbtLeadershipCollaboration
About this role
Thumbtack is a company that helps millions of people confidently care for their homes. They are seeking a Staff Data Engineer for their Marketing Technology team to design and maintain core marketing datasets and integrate data across various marketing functions to drive revenue growth.
Responsibilities:
- Collaboratively refine and evangelize a comprehensive framework for integrating data-thinking into the software development lifecycle for marketing
- Design, architect, and maintain core marketing 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 with teams consisting of product engineers, analysts, data scientists, machine learning engineers throughout marketing 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 marketing and business areas
- Help build the next generation of marketing data products at Thumbtack, based on real-time data products on top of Apache Kafka
Requirements:
- 8+ years of experience designing, building, and scaling data systems—spanning pipelines, warehouses, and analytical data products that drive measurable business impact
- Proven technical leadership in architecting and evolving complex data ecosystems, including ownership of data models, transformation frameworks, and integrations across multiple data domains; advanced proficiency in SQL and Python
- Deep experience with modern data stacks, including cloud-native warehouses (e.g., BigQuery or Snowflake), orchestration tools (Airflow or equivalent), and transformation frameworks (dbt or similar)
- Strong system design and architecture mindset, able to reason about scalability, cost, and performance trade-offs, and define long-term data strategy
- Exceptional collaboration and influence skills, partnering effectively with Marketing Engineering, Analytics, and Data Science to translate business goals into robust, production-grade data systems
- Strong sense of ownership and accountability, balancing hands-on technical execution with the ability to mentor others, raise standards, and drive organization-wide improvements in data quality and reliability