We’re looking for a senior-minded Nearshore engineer who can turn SAS-based logic into robust, governed Databricks pipelines using Python, SQL, and modern CI/CD practices—while maintaining strict delivery discipline.
Required experience
- 4+ years of professional data or software engineering experience.
- Strong Python and SQL skills.
- Hands-on Databricks experience with Unity Catalog, Workflows, and Databricks Asset Bundles.
- Proficiency with GitLab CI/CD (pipelines, merge request workflows, and automated testing) and disciplined Git branching and code reviews.
- Clear written and spoken English for client-facing collaboration.
- Demonstrated ownership: scoping work, delivering outcomes, and proactively flagging risks without being prompted.
Focus areas
- Pipeline reliability, validation, and delivery of converted code.
- Parity checks between SAS and Databricks outputs.
- Deployment and governance using DABs + GitLab CI/CD + Unity Catalog.
Additional experience
- Spark and Delta Lake performance tuning.
- Data validation and reconciliation experience.
- Infrastructure-as-code or DAB-based deployment experience.
- SAS reading ability and exposure to healthcare data (plus experience with Azure) are valued.
How we work: We value clarity, accountability, and continuous improvement. We’ll expect you to communicate trade-offs, confirm assumptions early, and build trust through predictable delivery, thoughtful reviews, and transparent risk management.
We’ll rely on you to drive the end-to-end conversion delivery from SAS inventories to validated Python/SQL outputs on Databricks, with a strong focus on pipeline reliability and data validation.
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Pipeline engineering: Build and run pipelines that process SAS inventories and produce converted outputs.
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Quality and parity validation: Validate converted code for parity against SAS outputs (e.g., row counts, checksums, schema, and data types).
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Deployment ownership: Own deployments through Databricks Asset Bundles (DABs) and GitLab CI/CD, ensuring repeatable releases.
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Databricks governance: Manage Unity Catalog objects, permissions, and promotion across environments.
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Operational excellence: Troubleshoot job failures and performance issues, and take preventive actions to improve pipeline stability.
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Performance tuning: Apply tuning techniques for Apache Spark and Delta Lake to meet reliability and execution-time expectations.
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Data reconciliation: Use data validation and reconciliation practices to ensure correctness and consistency.
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Infrastructure-as-code mindset: Implement DAB-based deployment patterns and support automated, testable delivery workflows.
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Client collaboration: Communicate progress, risks, and technical decisions clearly with client and partner stakeholders.
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Experience converting SAS workflows to Python/SQL in production environments.
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Healthcare data exposure and familiarity with typical data quality and privacy expectations.
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Azure exposure and understanding of how cloud services fit into end-to-end delivery and operations.
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Deep experience optimizing Spark jobs (partitioning, caching strategies, skew handling) and Delta Lake (file sizing, compaction patterns).
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Contrato a largo plazo.
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100% Remoto.
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Vacaciones y PTOs
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Posibilidad de recibir 2 bonos al año.
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2 revisiones salariales al año.
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Clases de inglés.
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Equipamiento Apple.
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Plataforma de cursos en linea
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Budget para compra de libros.
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Budget para compra de materiales de trabajo
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mucho mas..
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