Data Engineer (Databricks + Python + Azure)

Role & Responsibilities:

• Design, develop, and maintain scalable data pipelines using Databricks (PySpark) and Python.
• Build and optimize ETL/ELT processes within Azure cloud environments.
• Implement data models following modern Data Lakehouse principles (e.g., Medallion architecture).
• Ensure data quality, consistency, and performance across ingestion, staging, and curated layers.
• Collaborate with data architects, analysts, and business stakeholders to translate healthcare data requirements into technical solutions.
• Develop reusable data transformation logic and modular processing components.
• Support deployment processes following CI/CD and DevOps best practices.
• Monitor and optimize data workflows for performance, scalability, and reliability.
• Contribute to data governance, security, and compliance practices relevant to healthcare environments.

Hard Skills - Must have:

• Current knowledge of and using modern data tools like Databricks, FiveTran, Data Fabric and others.
• Core experience with data architecture, data integrations, data warehousing, and ETL/ELT processes.
• Applied experience with developing and deploying custom whl and or in session notebook scripts for custom execution across parallel executor and worker nodes.
• Applied experience in SQL, Stored Procedures, and PySpark based on area of data platform specialization.
• Strong knowledge of cloud and hybrid relational database systems, such as MS SQL Server, PostgreSQL, Oracle, Azure SQL, AWS RDS, Aurora or a comparable engine.
• Strong experience with batch and streaming data processing techniques and file compactization strategies.

Hard Skills - Nice to have/It's a plus:

• Strong hands-on experience with Databricks in Azure environments.
• Advanced proficiency in Python and PySpark for distributed data processing.
• Experience building and optimizing data pipelines in Azure (Azure Data Factory, Azure SQL, Data Lake Storage, etc.).
• Solid understanding of data warehousing, data lakehouse concepts, and ETL/ELT frameworks.
• Experience working with relational databases such as SQL Server, PostgreSQL, Oracle, or similar.
• Knowledge of batch and streaming data processing patterns.
• Experience working with large, complex datasets in cloud-based distributed environments.

Soft Skills / Business Specific Skills:

• Strong analytical and problem-solving skills.
• Ability to work effectively in cross-functional and distributed teams.
• Clear communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Proactive mindset with a strong sense of ownership.
• Commitment to delivering high-quality, reliable data solutions.