Senior Data Engineer designing and developing scalable data pipelines using Azure Databricks and BI architectures. Collaborating for healthcare analytics and decision-making in a hybrid workplace.
Responsibilities
Design, develop, test, and deploy robust and scalable data pipelines using Azure Databricks, PySpark, and Spark SQL for processing large volumes of structured and unstructured data.
Implement workflow orchestration using Azure Data Factory and Databricks Workflows to automate ETL/ELT processes.
Implement and maintain CI/CD pipelines for Databricks notebooks, scripts, and configurations using Azure DevOps or GitHub Actions, promoting code across dev, test, and prod environments.
Develop and maintain healthcare data models, including data entities, relationships, and data flows, to support healthcare analytics and decision-making.
Design and implement enterprise-wide BI architectures. Develop and maintain data warehouses and data marts.
Develop and maintain reports, dashboards, and data visualizations. Collaborate with stakeholders to understand business needs and provide data-driven insights
Requirements
6+ years of experience as a Data Engineer with a proven track record of building data pipelines in the cloud.
3+ years of hands-on experience with **Azure Databricks**
Strong experience with core Azure data services – Azure Data Lake Storage (Gen 2), Azure data factory.
Proficiency in **Python** and expert-level skills in **SQL**
Solid understanding of data warehousing concepts, dimensional modeling (star/snowflake schemas), and data architecture principles
Experience with CI/CD pipelines (Azure DevOps, Jenkins, GitHub Actions) and version control systems (Git).
Demonstrated experience and knowledge of strategic problem solving and frameworks, and project management skills
Excellent written and verbal communication with the ability to establish credibility and strong relationships with stakeholders
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