Senior Data Engineer – Databricks, Azure
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Job Description
Databricks Expert Engineer role developing Azure Databricks pipelines for Johnson & Johnson's healthcare project. Working on ETL processes and collaborating with cross-functional teams to optimize data workflows.
Responsibilities:
- Design, build, and optimize Databricks pipelines in an Azure environment
- Develop reliable ETL/ELT workflows using PySpark / Spark SQL
- Implement and maintain data ingestion from multiple sources (APIs, DBs, cloud storage, etc.)
- Improve performance, scalability, and cost-efficiency of Databricks workloads
- Work with stakeholders to translate business needs into technical solutions
- Ensure best practices around data quality, monitoring, documentation, and maintainability
- Collaborate with cross-functional teams (data engineering, analytics, product, etc.)
Requirements:
- Proven experience as a Databricks Engineer (expert-level)
- Strong hands-on work in Azure Databricks
- Advanced Spark / PySpark and SQL
- Experience with Azure Data Lake / Blob Storage and Azure-native data workflows
- Solid understanding of data engineering fundamentals (batch processing, orchestration, data modeling basics)
- Comfortable working independently in fast-moving, delivery-focused projects
- English communication skills (written + verbal) for working with global teams
- Nice to Have
- Experience with Delta Lake and lakehouse patterns
- Familiarity with orchestration tools (e.g., ADF, Airflow, etc.)
- CI/CD exposure for data pipelines (Azure DevOps, Git-based workflows)
- Experience supporting analytics/reporting or downstream ML use cases
Benefits:
- Fully remote contractor role (LATAM-friendly)
- Opportunity to work with a global healthcare leader
- High chance of extension after the initial contract
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