Data/Software Engineer (Sas→Python)

Required both

• 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.

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

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

We are Improving, an IT services firm focused on AI, Data, and Applications. We modernize legacy systems, build cloud-native platforms, and deliver future-ready solutions through collaborative, long-term partnerships that drive measurable outcomes. In this role, we’ll support a team converting existing SAS code to Python and SQL on Databricks using generative AI. You’ll work with the existing accelerators, take ownership of your deliverables end to end, and partner closely with client and stakeholder teams to ensure reliable pipeline execution, accurate validation, and dependable delivery of converted code across the data lifecycle.