Data Engineer Azure Databricks

Location:

100% Remote

Employment Type:

Contract

Pay Rate: $45 $ 55 per hour, based on experience

Work Authorization Requirement:
Candidates must be legally authorized to work in the United States without current or future sponsorship. Additional eligibility requirements may apply based on the nature of the clients work.

A leading global aerospace and defense technology organization is seeking a Data Engineer to support its Enterprise Services Infrastructure team.

This role will focus on designing and maintaining enterprise data pipelines in Azure Databricks. The Data Engineer will integrate data from Microsoft 365, Service Now, Splunk, identity platforms, endpoint technologies, and cybersecurity systems into analytics-ready Delta Lake tables.

The position will also support data governance, lineage, semantic search, natural-language analytics, and applied AI initiatives. This is an excellent opportunity for a developing Data Engineer who wants hands‑on experience with enterprise‑scale data, modern Lakehouse architecture, and emerging AI technologies.

• Design, build, and maintain enterprise data pipelines using Azure Databricks.
• Integrate Service Now, Splunk, Microsoft 365, identity, endpoint, infrastructure, and cybersecurity data.
• Use Python, PySpark, and Spark SQL to transform raw data into analytics‑ready Delta Lake tables.
• Develop scalable ETL and ELT workflows using Delta Lake and medallion architecture.
• Build Bronze, Silver, and Gold data layers to support analytics, reporting, and machine learning use cases.
• Create and maintain data models that support Power BI reporting, operational analytics, and business decision‑making.
• Build automated data‑quality checks, validation processes, monitoring, and error handling.
• Develop data‑lineage and governance solutions to identify upstream dependencies, downstream writes, undocumented transformations, stale datasets, ownership gaps, and redundant data products.
• Help create semantic data catalogs that allow users to identify authoritative datasets and understand their business context.
• Support natural‑language analytics solutions that help users find relevant data and generate grounded analytical queries.
• Contribute to retrieval‑augmented generation solutions that connect current Service Now incidents with relevant historical resolutions.
• Use vector embeddings, semantic search, metadata filtering, similarity matching, and clustering to improve enterprise knowledge management.
• Help identify stale, duplicate, underused, missing, or low‑quality knowledge articles.
• Collaborate with infrastructure, identity, service desk, governance, cybersecurity, and analytics teams.
• Translate operational challenges into scalable data products, reporting solutions, automation, and applied AI use cases.
• Document pipelines, data models, transformations, dependencies, and engineering processes.

• Approximately three or more years of hands‑on data engineering experience.
• Strong Python and SQL development skills.
• Hands‑on experience building data pipelines in Azure Databricks or a comparable Databricks environment.
• Experience with PySpark, Spark SQL, Databricks notebooks, and Delta Lake.
• Experience developing ETL or ELT pipelines and automated data workflows.
• Understanding of medallion architecture and Bronze, Silver, and Gold data layers.
• Experience with data modeling, data warehousing, schema design, and analytics‑ready datasets.
• Experience building data‑quality validations, monitoring, and error‑handling processes.
• Ability to explain previous Databricks projects and individual technical contributions.
• Must be legally authorized to work in the United States without current or future sponsorship and meet…