Job description

About Gridware Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware’s advanced Active Grid Response platform uses high-precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate-tech and Silicon Valley investors. For more information, please visit www.Gridware.io . Role Overview As a Data Engineer at Gridware, you’ll help build and maintain the pipelines and data systems powering our Active Grid Response platform. You’ll work closely with cross-functional engineers to ensure telemetry, sensor data, and operational information flows reliably through our Lakehouse and into analytics and monitoring tools. This is a hands-on, high-growth role ideal for engineers ready to deepen their expertise in distributed data systems. Responsibilities 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 Required Skills 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.) Understanding of event-driven systems or streaming platforms (Kafka, Kinesis, Pub/Sub) Solid foundation in data modeling, testing, and version control Ability to work collaboratively in a high-autonomy, fast-paced environment Bonus Skills Experience with IoT, telemetry ingestion, or time-series data Exposure to Unity Catalog, governance, or schema enforcement Understanding of Protobuf, Avro, Parquet, or serialization formats Hands-on experience with observability tools (Grafana, OpenTelemetry) **At this time, Gridware is unable to provide visa sponsorship or immigration support for this role. We’re only able to consider candidates who are currently authorized to work in the country of employment without visa sponsorship now or in the future.** This describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply! Gridware Technologies Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state, or local law. Benefits Health, Dental & Vision (Gold and Platinum with some providers plans fully covered) Paid parental leave Alternating day off (every other Monday) “Off the Grid”, a two week per year paid break for all employees. Commuter allowance Company-paid training

Requirements

Must-haves

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
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.)
Understanding of event-driven systems or streaming platforms (Kafka, Kinesis, Pub/Sub)
Solid foundation in data modeling, testing, and version control
Ability to work collaboratively in a high-autonomy, fast-paced environment
Experience with IoT, telemetry ingestion, or time-series data
Exposure to Unity Catalog, governance, or schema enforcement
Understanding of Protobuf, Avro, Parquet, or serialization formats
Hands-on experience with observability tools (Grafana, OpenTelemetry)
This describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply!
Gridware Technologies Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state, or local law.

Nice-to-haves

Bonus Skills

Application prep

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Keywords to mirror

pythonsql

Platform: lever
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Parental Leave