Data Engineer at Motive delivering data infrastructure for the AI era. Collaborating with stakeholders, building models, and implementing innovative tooling.
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
Requirements
- 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
Benefits
- Choice of medical, dental, and vision insurance plans for you and your family
- Additional insurance coverage options for life, accident, or critical illness
- Flexible paid time off, sick leave, short-term and long-term disability
- 10 US observed holidays, and Canadian statutory holidays by province
- A home office stipend
- 401(k) for US-based employees and RRSP for Canada-based employees
- Paid parental leave
- A local in-person meet-up program
- Hubs in San Francisco and Toronto
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