Data Engineer
Gridware, San Francisco, CA
What you will do
- Building ETL/ELT pipelines that ingest transformer, pole, and sensor telemetry into Gridware’s Data Lake and Lakehouse
- Developing and maintaining real-time and batch ingestion processes using Python, SQL, Databricks, and Spark
- Implementing data quality checks, validation rules, and automated testing for stable operations
- Collaborating with Software, Firmware, and Data Science teams to define ingestion schemas and transformations
- Working with cloud-native tools to optimize pipeline throughput and cost efficiency
- Monitoring pipelines for reliability, troubleshooting issues, and contributing to on-call rotations
- Writing documentation for data processes, models, and metadata
What you need
- 2–4 years of experience as a Data Engineer (or Backend Engineer with heavy data exposure)
- Strong proficiency in Python and SQL
- Familiarity with data warehouses, Lakehouse platforms, or big data tools (Databricks, Spark, or equivalent)
- Experience with pipeline orchestration tools (Airflow, Dagster, Prefect, etc.)