Responsibilities

Build and maintain ETL/ELT pipelines that move and transform data reliably across our stack
Model clean, well-documented datasets to support analytics, reporting, and experimentation
Collaborate with data analysts and product teams to improve data quality and accessibility
Contribute to data quality monitoring and alerting to catch issues early
Help instrument new product features and events alongside engineering and product teams
Write readable, tested, well-documented SQL and Python code
Participate in code reviews, give and receive constructive feedback
Learn from senior engineers and contribute ideas to how we build and scale our data infrastructure

Requirements

1–4 years of experience in data engineering, analytics engineering, or a related role
Solid SQL skills and working knowledge of Python
Familiarity with data warehousing concepts and how data flows through a modern stack
Some hands-on experience with tools like dbt, Airflow, Terraform, Snowflake, BigQuery, or Redshift
Experience with data platforms in a cloud environment (AWS, Azure, or GCP)
A curiosity-driven mindset — you ask questions, dig into problems, and enjoy figuring things out
Good communication skills and comfort working cross-functionally
Willingness to take ownership of tasks and follow through