About the role

Senior Data Engineer building and scaling data platforms for analytics and business intelligence. Join our mission to close the justice gap using technology and AI.

Responsibilities

Build and scale the data platform that powers analytics, experimentation, and business intelligence across the organization
Design and maintain robust, well-documented ELT/ETL pipelines and reusable data models
Partner cross-functionally with Product, Engineering, Operations, and Analytics teams to translate business needs into scalable data solutions
Own the design and implementation of data pipelines supporting product instrumentation, reporting, and experimentation
Establish and maintain high standards for data quality, reliability, governance, and observability
Contribute to a strong data engineering culture through mentorship and best practices
Build and maintain scalable data pipelines and infrastructure using tools such as dbt, Airflow or Dagster, and BigQuery, Snowflake, or similar technologies
Ensure reliability, documentation, and performance at scale
Improve data reliability by implementing testing, monitoring, and observability best practices to reduce human error and ensure trust in data outputs
Support business intelligence and experimentation efforts by building data models and enabling reporting and dashboarding solutions using tools such as Looker, Tableau, or Metabase
Mentor engineers and analysts on data modeling standards, tooling, and engineering best practices while helping shape a strong, collaborative data culture

4+ years of experience as a Data Engineer or Software Engineer, ideally in product-focused, high-growth environments
Strong proficiency in Python for data wrangling, orchestration logic, and navigating application codebases
Strong proficiency in SQL and experience using transformation tools such as dbt to build reusable data models
Experience designing dimensional models and defining clear, trusted business metrics
Experience building scalable, reliable data pipelines in modern cloud environments
Familiarity with data warehouse technologies such as BigQuery or Snowflake and orchestration tools such as Airflow or Dagster
Experience enabling reporting and visualization solutions using dashboarding tools (e.g., Looker, Tableau, Metabase)
Strong communication and collaboration skills when working with cross-functional stakeholders
High attention to detail, structured thinking, and a bias toward action in fast-paced environments
Leadership potential with interest in mentoring others and shaping data engineering best practices