Hands-on AWS Data Engineer to design, build, and optimize scalable data pipelines. Will use Python/Golang to engineer serverless ETL solutions, manage secure data lakes, and resolve complex architectural challenges independently with minimal supervision.
Key Responsibilities

• Pipeline Development: Build, maintain, and scale robust data ingestion and processing pipelines using Lambda, API Gateway and AWS Glue.
• Architecture & Infrastructure:Provision and manage infrastructure-as-code (IaC) using AWS CloudFormation.
• Data Management & Governance:Design and implement data storage/retrieval solutions leveraging DynamoDB and build compliant data governance frameworks via Lake Formation.
• Security: Implement strict access control, masking, and least-privilege security policies using AWS IAM.
• Troubleshooting:Independently analyze, debug, and resolve data pipeline or infrastructure issues with high autonomy and quick problem-solving skills.
• Collaboration: Partner with cross-functional teams, acting as a supportive team member who effectively communicates technical roadblocks and solutions.

Required Skills & Qualifications

• Core Languages: Strong programming proficiency in Python or Golang.
• AWS Compute & API: Deep hands-on experience with AWS Lambda, API Gateway, and DynamoDB.
• Data Engineering & Governance:Advanced knowledge of AWS Glue, IAM, and Lake Formation.
• Infrastructure as Code (IaC): Proven track record building and updatingCloudFormation templates.
• Soft Skills: Exceptional communication skills, a proactive "hands-on” attitude, strong analytical problem-solving, and the ability to troubleshoot independently with minimal support.

Preferred Qualifications

• Additional Cloud Services:Familiarity with AWS Step Functions, S3 lifecycle policies, and Amazon CloudWatch.
• Data Warehousing: Prior experience working with Amazon Redshift or Athena is a plus.