Data Engineer

Leidos is seeking a Data Engineer to support the National Healthcare Safety Network (NHSN) support contract on a strategic modernization initiative to migrate SAS datasets, ETL processes, and analytical workloads to the Databricks Lakehouse Platform. This role will be responsible for converting legacy SAS data processing into scalable PySpark and SparkR solutions while ensuring data integrity, performance, and business rule consistency.

The ideal candidate has experience with both SAS and modern distributed data processing frameworks and can translate complex SAS workflows into optimized Databricks implementations.

Primary Responsibilities:

• Migration of SAS datasets, ETL workflows, and data transformation logic to Databricks.
• Convert SAS programs, DATA steps, PROC SQL, and macros into PySpark and SparkR code.
• Develop scalable data pipelines using Apache Spark within the Databricks environment.
• Design and optimize Delta Lake tables for performance, reliability, and scalability.
• Validate migrated datasets through automated reconciliation and data quality testing.
• Partner with business analysts, data scientists, and application teams to ensure functional equivalence between SAS and Databricks solutions.
• Optimize Spark jobs for performance, partitioning, and resource utilization.
• Develop reusable frameworks, utilities, and coding standards to accelerate migration efforts.
• Document data lineage, transformation logic, and technical designs.
• Participate in code reviews and implement CI/CD practices using Git and Azure DevOps (or similar tools).

Required Qualifications:

• Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, or a related discipline.
• 5+ years of experience in Data Engineering or ETL development.
• Strong experience developing with SAS (Base SAS, DATA Step, PROC SQL, SAS Macros).
• Hands-on experience with Databricks.
• Strong proficiency in PySpark and/or SparkR.
• Advanced SQL development skills.
• Experience with Delta Lake architecture and Spark optimization techniques.
• Experience building and maintaining enterprise-scale data pipelines.
• Knowledge of data modeling, data warehousing, and distributed computing principles.
• Experience with Git and CI/CD deployment processes.

Preferred Qualifications:

• Previous experience leading enterprise SAS modernization initiatives.
• Experience migrating SAS datasets and business logic to Databricks.
• Experience with Unity Catalog, Delta Live Tables, and Databricks Workflows.
• Familiarity with Azure Data Factory, Azure Synapse, or other cloud-native data integration services.
• Experience working with large-scale healthcare, insurance, or financial datasets.
• Knowledge of data governance, security, and regulatory compliance requirements.
• Experience implementing automated testing and data validation frameworks.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares.

Original Posting:

July 29, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $87,100.00 - $157,450.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.