Data Engineer

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)