remote
Staff Analytics Engineer - Aurora Solar
Data Engineer
Lead the design and implementation of scalable data pipelines and analytics platforms, leveraging Python, SQL, dbt, Snowflake, Airflow, and Looker to deliver actionable insights for solar industry solutions.
About the role
Key Responsibilities
- Architect, build, and maintain robust, high‑performance data pipelines that ingest, transform, and store large volumes of solar design and performance data.
- Develop and optimize dbt models and Snowflake schemas to ensure clean, reliable, and query‑efficient data for downstream analytics.
- Design and implement monitoring, alerting, and data quality frameworks using Airflow and AWS services.
- Collaborate with product, engineering, and data science teams to translate business requirements into scalable analytical solutions and visualizations in Looker.
- Mentor junior engineers, establish best practices, and drive continuous improvement of the analytics stack.
Requirements
- 5+ years of experience building data pipelines and analytics platforms in a cloud environment, preferably AWS.
- Strong proficiency in Python and SQL, with hands‑on experience in dbt, Snowflake, and Airflow.
- Demonstrated ability to design data models, ensure data quality, and optimize query performance.
- Experience creating dashboards and self‑service analytics using Looker or similar BI tools.
- Excellent problem‑solving skills, ability to work cross‑functionally, and a passion for renewable energy data.
Skills
pythonsqldbtsnowflakeairflowlookeraws