Overview
Skills
Job Details
Senior Data Engineer Azure, Databricks, PySpark
Location: Hybrid (3 days a week onsite)
Duration: 12-Month Contract (with potential extensions)
Industry: Healthcare
Overview:
We are seeking a Senior Data Engineer with strong expertise in Azure, Databricks, and PySpark to join a high-impact healthcare data team. This is a great opportunity to work with a large enterprise organization on mission-critical data transformation and analytics initiatives. The ideal candidate will be experienced in cloud data engineering, automation, and building scalable data pipelines that deliver real business value.
Key Responsibilities:
- Build and maintain scalable ETL/ELT pipelines using Databricks (PySpark) on Azure.
- Automate data ingestion and transformation from diverse structured and unstructured sources.
- Ensure high availability, performance, and reliability of data platforms.
- Support business analytics and reporting by enabling fast and secure data access.
- Work with SQL Server Integration Services (SSIS), SQL, and cloud-native tools.
- Collaborate cross-functionally with data architects, data analysts, and engineering teams.
Required Skills & Qualifications:
- 8 10 years of hands-on experience in data engineering roles.
- Expert-level experience with Azure Data Services (e.g., Data Lake, Data Factory, Synapse).
- Strong hands-on experience with Databricks and PySpark for big data processing.
- Solid experience with SQL, ETL/ELT pipeline development, and SSIS.
- Experience with cloud and hybrid data architecture.
- Familiarity with Hadoop or Snowflake environments.
- Excellent communication, problem-solving, and organizational skills.
Preferred Skills:
- Proficiency in Python, NoSQL, and data movement tools.
- Knowledge of data modeling, data governance, and best practices in data quality.
- Experience with data exchange formats (JSON, XML).
- Exposure to Power BI is a plus.
Education:
Bachelor s degree in computer science, Information Technology, Engineering, or a related field.