
Job Summary:
As an AWS Data Engineer, you will be responsible for designing, developing, and maintaining scalable, high-performance data pipelines using AWS services. With 6+ years of experience, you’ll collaborate closely with data architects, analysts, and business stakeholders to build reliable, secure, and cost-efficient data infrastructure across the organization.
Key Responsibilities:
- Design, develop, and manage scalable data pipelines using AWS Glue, Lambda, and other serverless technologies
- Implement ETL workflows and transformation logic using PySpark and Python on AWS Glue
- Leverage AWS Redshift for warehousing, performance tuning, and large-scale data queries
- Work with AWS DMS and RDS for database integration and migration
- Optimize data flows and system performance for speed and cost-effectiveness
- Deploy and manage infrastructure using AWS CloudFormation templates
- Collaborate with cross-functional teams to gather requirements and build robust data solutions
- Ensure data integrity, quality, and security across all systems and processes
Required Skills & Experience:
- 6+ years of experience in Data Engineering with strong AWS expertise
- Proficient in Python and PySpark for data processing and ETL development
- Hands-on experience with AWS Glue, Lambda, DMS, RDS, and Redshift
- Strong SQL skills for building complex queries and performing data analysis
- Familiarity with AWS CloudFormation and infrastructure as code principles
- Good understanding of serverless architecture and cost-optimized design
- Ability to write clean, modular, and maintainable code
- Strong analytical thinking and problem-solving skills

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