Data/Software Engineer (Sas→Python)

Pipeline reliability, validation, and delivery of converted code.

• Build and run the pipelines that process SAS inventories and converted outputs.

• Validate converted code for parity against SAS outputs (row counts, checksums, schema, data types).

• Own deployment through Databricks Asset Bundles (DABs) and GitLab CI/CD.

• Manage Unity Catalog objects, permissions, and environment promotion.

• Troubleshoot job failures and performance issues.

• Perform Spark and Delta Lake performance tuning.

• Apply data validation and reconciliation practices to ensure correctness.

• Use Infrastructure as Code or DAB-based deployment approaches.

You’ll also communicate directly with client and partner stakeholders and coordinate deliverables with clear ownership from scoping through delivery, including proactive risk flagging.

• 4+ years of professional data or software engineering experience.

• Strong Python and SQL.

• Hands-on Databricks experience, including Unity Catalog , Workflows , and Databricks Asset Bundles .

• GitLab CI/CD experience: pipelines, merge request workflows, and automated testing.

• Git branching and code review discipline.

• Clear written and spoken English for client-facing collaboration with partners.

• Demonstrated ownership: scoping, delivering, and flagging risk without prompting.

We’re looking for someone who can ensure the reliability of converted pipelines —not only writing code, but also validating results and operating deployments responsibly. You should be comfortable investigating failures, improving performance, and maintaining high standards for correctness and reproducibility in a collaborative environment.

• Ability to read SAS.

• Healthcare data exposure.

• Azure experience.

Any experience that helps you quickly understand legacy SAS logic, map it to Python/SQL equivalents, and collaborate across environments will be a plus.