DataBricks Data Engineer USA

· Technical specifications

· Solution designs

· Data flow documentation

· Pipeline documentation

· Data mapping documentation

· Databricks job orchestration documentation

· Databricks automation and workflow designs

· Databricks workflow configurations

· Deployment documentation

· Reporting outputs

· Technical status reports

Example activities

· Project coordination

· Business analysis

· Process improvement

· Operational readiness activities

· Reporting support

· Meeting facilitation

· Documentation support

· Stakeholder engagement

· Training and change support

· Cross-functional coordination

· Analysis reports

· Project plans

· Process maps

· Status reports

· Presentations

· Training materials

· Transition plans

· Readiness assessments

6–9 years of overall experience in data engineering, with strong hands-on experience in Databricks.

Solid proficiency in Apache Spark (PySpark and/or Scala) and SQL.

Proven experience supporting and optimizing production Databricks workloads (jobs, notebooks, Delta Lake, workflows).

Strong understanding of Delta Lake concepts (ACID transactions, time travel, optimization techniques such as Z-ordering, vacuum, optimize).

with Databricks Job clusters, Interactive clusters, and performance tuning (partitioning, caching, shuffle optimization, autoscaling).

Familiarity with data modeling, ETL/ELT patterns, and production data pipeline support.

working with cloud platforms (preferably Azure, AWS, or GCP) in the context of Databricks.

Ability to troubleshoot complex Spark and Databricks issues independently.

Strong communication skills and ability to work effectively in a remote, EST-aligned team.

Experience with Unity Catalog, Databricks SQL, or Lakehouse architecture.

Knowledge of CI/CD practices for Databricks (e.g., Databricks Asset Bundles, Git integration, Terraform/ARM templates).

Familiarity with orchestration tools (Airflow, Azure Data Factory, or Databricks Workflows).

Exposure to data quality frameworks, monitoring tools, or cost optimization initiatives on Databricks.

supporting analytics or BI teams consuming Databricks data products.

Fully remote

Must be available and productive during EST business hours

Collaborative remote environment with regular syncs and support responsibilities