Develop, test, and maintain data pipelines and DBT models to ensure reliable data flow across systems.
Collaborate with analysts to structure datasets that are optimized for reporting and activation.
Support data quality checks, monitoring, and documentation to maintain trust in our data.
Assist with data integrations across tools like Google Tag Manager, Hightouch, Segment, and Braze.
Work with senior engineers to understand our data architecture and best practices.
Partner with marketing, product, and operations teams to help deliver data for targeting, personalization, and measurement.
Participate in code reviews, team discussions, and continuous improvement initiatives.
Troubleshoot data issues, track root causes, and propose solutions.
Help improve workflow automation.
Contribute to documentation and internal guides for the data team.

1–2 years of experience in data engineering, analytics engineering, or a related technical field
Solid understanding of SQL and foundational-to-intermediate level of Python for data manipulation and ETL processes
Familiarity with cloud data warehouses (preferably BigQuery) and version control (Git)
Ideally some basic knowledge of DBT, reverse ETL, and workflow orchestration tools (e.g., Prefect, Airflow)
Strong problem-solving skills and curiosity for how data moves through systems
Comfortable working in a remote, fast-paced, startup environment.

Data Engineer

Key skills