About Our Client:
Johnson & Johnson is one of the world’s most respected and innovative healthcare companies, dedicated to improving the health and well-being of people everywhere. With a integral presence across pharmaceuticals, medical devices, and consumer health, J&J; is known for combining science, technology, and design to deliver impactful solutions.
About the Role:
We’re looking for a Databricks Expert Engineer with strong experience in the Azure ecosystem to support a high-impact project. This is a contractor role through Workana, starting ASAP, with a 3-4 month initial contract and strong potential for extension.
What You’ll Do:
- 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

Benefi

📌 Senior Data Engineer (México)
🏢 Workana
📍 México