AWS Data Engineer

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Essential Requirements

• 6–7 years of IT experience with minimum 3 years in Data Engineering / Data Architecture (data lakes, ingestion, extraction, transformation).
• Strong hands-on expertise in AWS cloud technologies including:
• AWS Lambda, S3, DynamoDB, EC2, ECS, ECR, CloudFormation
• AWS Glue, Glue Catalog, Athena, DMS
• Proficiency in Python and PySpark for data processing and automation.
• Solid experience with SQL and PL/SQL concepts.
• Experience in data ingestion, transformation, and orchestration pipelines.
• Hands-on experience in building data pipelines and applications to stream and process large datasets at low latencies.
• Exposure to Snowflake for cloud-based data warehousing.
• Self-starter with ability to quickly learn new technologies, multitask, and manage priorities effectively.
  

Key Responsibilities

• Design, develop, and maintain data pipelines and solutions leveraging AWS cloud services.
• Work on data ingestion, transformation, and orchestration frameworks to ensure scalability and performance.
• Implement best practices in data engineering, ensuring quality, security, and compliance with data regulations.
• Collaborate with architects and business stakeholders to design data lake / data warehouse solutions.
• Troubleshoot and optimize data pipelines for high availability and low-latency performance.
• Provide technical guidance on AWS services and data engineering frameworks to junior team members.