Description

You will design, build, and optimize large-scale data processing systems for healthcare analytics and operational reporting.

Responsibilities

• Design and implement ETL/ELT pipelines using Python and PySpark.
• Develop scalable data workflows using Apache Spark and AWS Glue.
• Collaborate with QA and DevOps to integrate CI/CD and testing automation.
• Manage data lake structures to ensure data quality, lineage, and auditability.
• Optimize and monitor performance for both batch and streaming pipelines.

Required Skills

• 5+ years of experience in data engineering roles.
• Deep proficiency in Python, PySpark, and SQL including Window functions and CASE statements.
• Hands-on experience with AWS Glue, S3, and Lambda.
• Experience with Apache Spark and Apache Airflow.
• Knowledge of Delta Lake and Data Lakehouse architecture.
• Ability to build infrastructure as code (IaC) using Terraform and GitHub Actions.
• Practical understanding of Kafka, data modeling, and normalization.
• Competency in Unix/Linux environments and Git version control.
• Understanding of AWS cloud storage, IAM, and networking fundamentals.

Preferred Skills

• Healthcare data domain knowledge.

Key Skills

Education

Any Gradute