Forward Deployed Data Engineer IV, Databricks
New
J
JobgetherEnergy and Utilities
Remote-based work within the United States.Full-TimeSenior
Salary$175,000–$200,000 USD plus an annual bonus
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSDockerPythonSQLGitData engineeringSparkCI/CDDatabricks
Requirements
- Bachelor’s degree in Computer Science, Information Technology, or related field.
- 5+ years of experience in data engineering, data platforms, or analytics engineering.
- Expert proficiency in Python, SQL, Databricks, and Spark.
- Experience building and operating cloud-based data pipelines in AWS.
- Knowledge of core data engineering challenges such as incremental processing, idempotency, and schema evolution.
- Experience designing both batch and streaming pipelines.
- Proficiency in Git, Docker, CI/CD tooling, and modern orchestration frameworks.
- Experience using AI coding assistants and agentic development tools.
- Experience managing the full system lifecycle and working directly with enterprise clients.
- Strong project delivery skills including managing technical scope and timelines.
- Strong communication skills for documentation and technical whiteboarding.
Responsibilities
- Embed directly with utility clients to design and build production data platforms covering ingestion, transformation, orchestration, quality, governance, and serving using Databricks, Spark, Python, SQL, and AWS.
- Own the technical architecture of client engagements from discovery through deployment, communicating and defending architectural decisions with client stakeholders.
- Lead technical discovery independently to identify business needs and recommend appropriate data solutions.
- Deliver functional systems early and harden them for production based on operational requirements.
- Lead migrations from legacy data warehouses to modern cloud platforms.
- Develop robust data models using dimensional, lakehouse, medallion, graph, or semantic approaches.
- Integrate utility operational systems such as SCADA, GIS, and ERP platforms via APIs and other mechanisms.
- Build observable pipelines with monitoring, alerting, and data quality controls for client maintenance.
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