Aws data engineer

Responsibilities and JD in brief along with additional criteria to be considered:

Design, develop and maintain scalable data pipelines on AWS. Build ETL/ELT workflows using AWS Glue, Python and Py Spark, with AWS S3 as the data-lake storage layer. Develop and optimize Databricks workloads and Delta Lake implementations. Write complex SQL queries for transformation, validation and performance optimization. Design logical and physical data models to support analytics and reporting requirements. Implement automated CI/CD pipelines using AWS Dev Ops services such as Code Pipeline, Code Build and Code Deploy. Apply Git-based version control and Dev Ops practices for build, deployment, monitoring and release management. Ensure data quality, security, governance, performance tuning and production support. Collaborate with architects, business stakeholders and downstream consumers in an Agile delivery model.

Any additional things to be checked:

Strong hands-on AWS data engineering experience, including AWS S3 and AWS Glue. Hands-on coding proficiency in Python, Py Spark and SQL. Experience in Databricks and Delta Lake-based data processing. Practical data-modeling experience for analytics and reporting use cases. Experience implementing CI/CD pipelines in AWS using Code Pipeline, Code Build, Code Deploy or equivalent tools. Working knowledge of Git and Infrastructure as Code using Terraform or AWS Cloud Formation. Good communication, problem-solving and client-interaction skills.

Location(s) where this position can work out of- Bangalore / Hyderabad

Desired experience range- 7 to 12 years

*Must have skills - 2 skills which are non-negotiable 1. AWS Glue , S3 2. Py Spark

*Desirable skills - 1 skill which is nice to have Databricks with Delta Lake