- You will work closely with data architects, analytics teams, and application developers to enable high-performance data processing and real-time analytics.

Required Skills & Experience :

- Strong programming skills in Python, including Pandas and SQL.

- Hands-on experience with PySpark and distributed data processing.

- Expertise in AWS cloud services particularly EMR, Glue, DynamoDB, Lambda, S3, IAM.

- Experience working with Databricks.

- Strong understanding of ETL/ELT design, data warehousing, and data modeling concepts.

- Ability to optimize big data jobs for performance and cost efficiency.

- Familiarity with version control systems (Git) and CI/CD tools.

About the Role :

- We are looking for a highly skilled AWS Data Engineer to design, build, and optimize scalable data pipelines and analytical solutions.

- The ideal candidate will have strong experience with distributed data processing, ETL/ELT

workflows, and AWS cloud-native services.

- You will collaborate with data architects, analytics teams, and application developers to enable high-performance data processing and real-time analytics across the organization.

- Perform data validation, performance tuning, and cost optimization for big data workloads.

- Develop and maintain data models, metadata, and documentation following best practices.

- Ensure data reliability, integrity, and security across cloud platforms.

- Participate in code reviews and continuous improvement initiatives using CI/CD and Git.

Required Skills & Experience :

- Strong programming skills in Python, including Pandas and SQL.

- Hands-on experience with PySpark and distributed data processing.

- Expertise with AWS cloud services, especially : EMR, Glue, Lambda, DynamoDB, S3, IAM

- Experience working with Databricks for data engineering and analytics.

- Strong understanding of ETL/ELT processes, data warehousing, and data modeling concepts.