About the role

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.
Responsibilities:

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.

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.

Nice to have:

• 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.

Benefits:

• Contrato a largo plazo.
• 100% Remoto.
• Vacaciones y PTOs.
• Posibilidad de recibir 2 bonos al año.
• 2 revisiones salariales al año.
• Clases de inglés.
• Equipamiento Apple.
• Plataforma de cursos en linea.
• Budget para compra de libros.
• Budget para compra de materiales de trabajo.
• Mucho más…

About the role

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.
Responsibilities:

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.

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.

Nice to have:

• 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.

Benefits:

• Contrato a largo plazo.
• 100% Remoto.
• Vacaciones y PTOs.
• Posibilidad de recibir 2 bonos al año.
• 2 revisiones salariales al año.
• Clases de inglés.
• Equipamiento Apple.
• Plataforma de cursos en linea.
• Budget para compra de libros.
• Budget para compra de materiales de trabajo.
• Mucho más…