Staff Data EngineerForm Energy is hiring a Staff Data Engineer to build the data systems behind our deployed energy storage projects, turning real-time field telemetry into reliable, trustworthy data the rest of the company can build on. As a hands-on senior individual contributor and technical lead, you'll build and operate our operational-telemetry data products and independently lead the design of novel data solutions, raising the bar for data reliability and engineering practice by example. Your focus starts with commercial project operational telemetry and is likely to extend into manufacturing and R&D data over time, working within our data engineering group and partnering closely with field operations, hardware and controls engineers, and the analysts and application teams who depend on your data. This is an exciting opportunity to help shape and be part of the growth of a fast-moving company with breakthrough technology and an incredible mission!Relocation assistance is available.Design, build, and operate the streaming and batch pipelines that turn real-time telemetry from deployed energy-storage systems into reliable, well-modeled, query-ready datasets, spanning ingestion, transformation, storage in open table formats, and serving to downstream consumers.Take a lead role across the operational-telemetry data products, building on and extending the core streaming platform rather than reinventing it.Independently lead the design of novel data solutions, producing technical design docs and RFCs and driving them to alignment across the data, applications, and field-facing stakeholders they touch.Model and serve time-series and event data for downstream analytics, monitoring, and applications, using open table formats (Iceberg / Delta Lake) and time-series stores.Build and maintain data orchestration (Dagster, Prefect, or Airflow) for workflows that are reliable, observable, and testable.Stand up and manage the AWS infrastructure and infrastructure-as-code (Pulumi and/or Terraform) your pipelines run on.Partner with field operations, hardware/controls engineers, and analytics/application consumers to translate operational needs into trustworthy, well-documented data.Share in an on-call rotation to keep ops-critical data flowing.Raise the engineering bar through code review, mentorship, and technical influence that reaches beyond the immediate team.Bachelor's degree in computer science, applied mathematics, software engineering, data engineering or computer engineering plus 7+ years of data or software engineering experience, including building and operating production data pipelines where reliability is operationally critical.Strong production programming in Python, Scala, Java, or Go.Hands-on experience with data transformation tools such as Apache Spark (PySpark and/or Scala) and dbt.Experience with open table formats such as Apache Iceberg or Delta Lake.Experience with streaming data systems, including Kafka and/or Kinesis.Experience with orchestration frameworks such as Dagster, Prefect, or Airflow.AWS experience, plus infrastructure-as-code with Pulumi and/or Terraform.A track record of independently leading the design of novel solutions, including preparing technical design docs and/or RFCs.Excellent communication and organizational skills, and comfort participating in an on-call rotation.Nice to have: Databricks and/or Snowflake; industrial IoT experience and edge protocols (MQTT, Modbus, OPC-UA); time-series databases (InfluxDB, TimescaleDB, ClickHouse, Druid); REST APIs and webhooks; energy, hardware, or other physical-systems domain background.
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