Description

You will lead data engineering initiatives, owning the architecture and delivery of scalable data pipelines in a healthcare context.

Responsibilities

• Build and maintain ETL/ELT pipelines using Apache Airflow, Talend, or Informatica on AWS, Azure, or GCP.
• Develop large-scale data processing solutions using PySpark, Apache Spark, Hadoop, and Hive.
• Implement CI/CD pipelines for data workflows to ensure automated and reliable deployments.
• Manage and optimize SQL and NoSQL databases for performance and scalability.
• Integrate AI/ML data preparation and real-time streaming using Kafka.

Required Skills

• 10+ years of experience in data engineering.
• Hands-on expertise with Apache Spark and PySpark for big data processing.
• Proficiency in cloud platforms: AWS, Azure, or GCP.
• Strong SQL skills and knowledge of relational and NoSQL database design.
• Experience with data orchestration tools like Apache Airflow, Talend, or Informatica.
• Practical experience implementing CI/CD for data workflows.
• Experience with Kafka for real-time data streaming.

Preferred Skills

• Understanding of healthcare data standards and compliance (HIPAA, HL7, FHIR).

Key Skills

Education

Any Graduate