Job Description
Key Skills: IAM, AWS, Python, AWS Lambda, Data Engineer, AWS S3, Spark
nRoles and Responsibilities:
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- Design, build, and maintain scalable data pipelines on AWS.n
- Develop ETL/ELT workflows using AWS Glue, Lambda, EMR, and Step Functions.n
- Develop data ingestion frameworks using Kinesis, Kafka, and SQS.n
- Build and optimize data lakes using S3, Glue Data Catalog, and Lake Formation.n
- Develop and maintain data warehousing solutions using Redshift and Snowflake.n
- Implement data quality checks, monitoring, logging, and CI/CD deployments.n
- Collaborate with analytics and business teams to deliver high-quality datasets.n
- Design, develop, and deploy solutions using appropriate tools, design principles, and coding standards.n
- Configure robotics processes and objects using core workflow principles, ensuring solutions are maintainable and easy to understand.n
- Understand existing processes and manage changing requirements through structured change control processes.n




- Troubleshoot day-to-day issues in data and automation processes and provide timely resolutions.n
- Maintain proper documentation for solutions, test procedures, and scenarios throughout UAT and Production phases.n
- Coordinate with process owners and business stakeholders to understand as-is processes and design appropriate automation workflows.n

nSkills Required:
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- 6+ years of strong hands-on experience with AWS Glue, S3, Lambda, IAM, and Step Functions.n
- Strong proficiency in Python, PySpark, SQL, and data transformation logic.n
- Experience with Redshift, Athena, and Glue Data Catalog.n
- Strong knowledge of Apache Spark and distributed data processing using EMR/Glue.n
- Experience with data ingestion technologies such as Kinesis, Kafka, or SQS.n
- Valuable understanding of data modeling, data lake architecture, and data engineering best practices.n
- Experience implementing data quality, monitoring, logging, and CI/CD processes.n
- Familiar

📌 AWS Data Engineer_102637 (New Delhi)
🏢 MyCareernet
📍 New Delhi