Senior Data Engineer

1.Role : AWS Data Engineer :

Location : - Chennai, Hyderabad, Pune, Bangalore

Exp : - 6+ years

Work timings : - 2 to 11 PM

 Primary Skills : Python, Pyspark, Glue, Redshift, Lambda, DMS, RDS

,Cloud Formation and other AWS serverless ; Strong exp in SQL

Detailed JD

 Seeking a developer who has good Experience in Athena, Python code, Glue,

Lambda, DMS , RDS, Redshift Cloud Formation and other AWS serverless

resources.

 Can optimize data models for performance and efficiency. Able to write SQL

queries to support data analysis and reporting Design, implement, and

maintain the data architecture for all AWS data services.

 Work with stakeholders to identify business needs and requirements for data-

related projects Design and implement ETL processes to load data into the

data warehouse

 Good Experience in Athena, Python code, Glue, Lambda, DMS, RDS,

Redshift, Cloud Formation and other AWS serverless resources

2.Role : Senior Data Engineer - Azure

Experience Level : 5 - 8 Years; Location : Chennai

About the Role : We are seeking a highly skilled and experienced Data Engineer to join our

team, focusing on building and maintaining robust data pipelines and infrastructure for our U.S.

healthcare payer operations. You will be responsible for the ingestion, transformation, and

availability of large, complex healthcare datasets, enabling our data scientists and ML engineers

to develop impactful solutions. This role requires a strong foundation in data warehousing,

ETL / ELT processes, and cloud-based data platforms within a highly regulated environment.

Responsibilities :

• Design, develop, and optimize scalable data pipelines (ETL / ELT) to ingest, transform, and load

diverse healthcare data from various sources into our data warehouse / lake.

reporting, and machine learning initiatives.

validation, and transformation.

requirements and translate them into efficient data solutions.

sensitive healthcare data (e.g., HIPAA compliance).

improvement.

Required Technical Skills :

Experience with relational and NoSQL databases.

AWS S3, Redshift, Glue, EMR, Athena, Azure Data Lake, Azure Synapse Analytics, Azure Data

Factory).

deployments with AWS CodePipeline or alternatives.