Big Data Engineer - AWS Platform

Big Data AWS Engineer : Location : Bengaluru / Gurugram (Work from the Office).

Experience : 69 Years.

Employment Type : Full-Time.

About the Role :

We are looking for an experienced Big Data AWS Engineer to join our growing team and build scalable, cloud-native data platforms for the US Healthcare domain.

The ideal candidate will have strong expertise in AWS, Big Data technologies, and modern data engineering practices, with hands-on experience designing high-performance data pipelines and analytics solutions.

Key Responsibilities :

• Design, develop, and maintain scalable ETL pipelines and data integration solutions using AWS services.

• Build batch and real-time data processing applications using Apache Spark and Kafka.

• Develop and optimize data ingestion, transformation, and data lake solutions.

• Work with large healthcare datasets, including Claims, Membership, Benefits, Provider, Clinical, and Healthcare Analytics.

• Design efficient data models and support enterprise analytics platforms.

• Optimize SQL queries, indexing strategies, and overall data platform performance.

• Collaborate with architects, business analysts, and cross-functional teams to deliver data-driven solutions.

• Ensure data quality, governance, security, and compliance standards are met.

• Support production deployments, monitoring, troubleshooting, and performance tuning.

Required Skills & Experience : Mandatory Requirements :

• 69 years of experience in Big Data and Cloud Data Engineering.

• Minimum 3+ years of experience in the US Healthcare domain (Claims, Membership, Benefits, Provider, Clinical, or Healthcare Analytics).

• Strong hands-on experience with AWS and large-scale data processing platforms.

• Excellent problem-solving and analytical skills.

Technical Skills :

• AWS : Lambda, Glue, S3, EMR, RDS, IAM, CloudWatch.

• Big Data : Apache Spark, Spark Streaming, Kafka, Hive.

• Programming : Scala, Java, or Python.

• Databases : MySQL, PostgreSQL, Elasticsearch, NoSQL.

• Strong SQL, data modeling, query optimization, and indexing expertise.

• Linux/Unix shell scripting.

• Experience building both batch and real-time data processing pipelines.