Quick overview
Job description
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)
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