Only Immediate JoineesResponsibilities:Skills – AWS, DE, AirflowKey Responsibilities- Design, develop, and maintain data pipelines using AWS services such as Glue, Lambda, Step Functions, EMR, Kinesis, and S3. - Build and optimize data warehouses and data lakes on AWS (Redshift, Lake Formation). - Develop ETL/ELT jobs using PySpark, Spark, Python, and AWS native tools. - Implement best practices for data modeling, partitioning, performance tuning, and data lifecycle management. - Monitor and troubleshoot production pipelines ensuring high availability and reliability. - Collaborate with Data Architects, Analysts, and Business SMEs to translate requirements into technical solutions. - Ensure compliance with security, governance, and architecture standards. - Work with CI/CD tools for automation, deployment, and version control (CodePipeline, Git, CloudFormation/Terraform).Required Skills & Experience- 3–8 years of experience as a Data Engineer with strong AWS expertise. - Hands-on experience with: - AWS Glue (Jobs, Crawlers, Catalog) - Amazon Redshift / Redshift Spectrum - Amazon EMR / PySpark / Spark - AWS Lambda, S3, Athena, Kinesis - Strong proficiency in Python, PySpark, SQL, and data transformation techniques. - Experience with data lake, data warehouse, and streaming data architectures. - Solid understanding of cloud security, IAM, encryption, and networking basics. - Exposure to DevOps, CI/CD, and infrastructure-as-code tools.
Job Title
Data Engineer – AWS