AWS Data Engineer
About The Position
We are seeking an experienced AWS Data Engineer to design and implement robust data solutions. This role involves building and optimizing ETL pipelines, orchestrating complex workflows, and ensuring data quality and performance within our AWS environment. You will work with various AWS services, develop data models, and leverage Python, PySpark, and SQL for data transformation and automation. A strong background in data architecture, data modeling, and supply chain domain expertise is essential, along with experience in integrating with ERP systems and managing data governance.
Requirements
- Minimum Experience 8-10 years in Data Engineering or related roles
- Proven track record in AWSbased data solutions and orchestration
- Expertise in cloud to design build and maintain datadriven solutions
- Skilled in Data Architecture and Data Engineering with a strong background in Supply Chain domain
- Experienced in Data Modeling Conceptual Logical and Physical
- Experienced in ETL optimizations
- Experienced in Query optimizations and Performance tuning
- Technical Skills Languages Python PySpark SQL
- AWS Services Glue EMR EC2 Lambda DMS S3 Redshift RDS
- Data Governance Informatica CDGC
- CDQ
- DevOps Tools Git GitHub AWS CDK
- Security IAM encryption policies
- Monitoring CloudWatch Glue Catalog Athena
- Strong integration background with DB2 UDB SQL Server etc
Nice To Haves
- Integration with ERP systems SAP Homegrown ERP Systems APIbased Data Exchange between Manufacturing Supply Chain legacy applications and AWS pipelines
- Metadata Management for compliance attributes
- Audit Trails Reporting for compliance verification
Responsibilities
- Design and implement ETL pipelines using AWS services Glue EMR DMS S3 Redshift
- Orchestrate workflows with AWS Step Functions EventBridge and Lambda
- Integrate CICD pipelines with GitHub and AWS CDK for automated deployments
- Develop conceptual logical and physical data models for operational and analytical systems
- Optimize queries normalize datasets and apply performance tuning techniques
- Use Python PySpark and SQL for data transformation and automation
- Monitor pipeline performance using CloudWatch and Glue job logs
- Troubleshoot and resolve data quality and performance issues proactively
- Integrate with ERP systems SAP Homegrown ERP Systems APIbased Data Exchange between Manufacturing Supply Chain legacy applications and AWS pipelines
- Implement Metadata Management for compliance attributes
- Implement Audit Trails Reporting for compliance verification
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
