Data Engineer

Experience: 15+ YearsPETADATA is seeking a seasoned Senior Data Lake Engineer with over 15 years of experience in data engineering and a strong focus on building and managing AWS-native Data Lake solutions. The ideal candidate will have deep expertise with AWS Lake Formation, serverless data processing using Lambda and Python, and experience with AI-assisted development tools such as Amazon Q.

Responsibilities: Data Lake Architecture: Design, build, and optimize scalable, secure data lakes using AWS Lake Formation and best practices for data governance, cataloging, and access control. Serverless Development: Build and deploy AWS Lambda functions using Python for real-time data processing, automation, and event-driven workflows. ETL / ELT Pipelines: Develop and maintain robust data pipelines using AWS Glue, integrating data from various structured and unstructured sources. AI Tools for Development: Leverage AI-powered coding tools (such as Amazon Q, GitHub Copilot, or similar) to increase development speed, code quality, and automation. Database Integration: Design and implement integrations between the Data Lake and DynamoDB, optimizing for performance, scale, and consistency. Security & Compliance: Implement fine-grained access control using Lake Formation, IAM policies, encryption, and data masking techniques to meet enterprise and compliance standards (e.g., GDPR, HIPAA).Monitoring & Optimization: Implement logging, monitoring, and performance tuning for Glue jobs, Lambda functions, and data workflows. Collaboration & Leadership: Collaborate with cross-functional teams including data science, analytics, DevOps, and product teams. Provide mentorship and technical leadership to junior engineers.

Position: Senior Data Lake Engineer

Location: Dallas, TX (Remote)

Note: This role requires strong hands-on skills in AWS Glue, DynamoDB, and building secure, scalable, and automated data platforms that support advanced analytics and machine learning use cases.

Experience: 15+ years in data engineering roles, with 5+ years focused on AWS-native data lake development. Cloud Expertise: Deep, hands-on expertise in AWS Lake Formation, Glue, Lambda, and DynamoDB.Programming: Proficient in Python, especially for serverless and data processing applications. AI Coding Tools: Experience using AI-assisted development tools (e.g., Amazon Q, GitHub Copilot, AWS CodeWhisperer).Security: Strong knowledge of data security practices in AWS, including IAM, encryption, and compliance standards. Orchestration & Automation: Experience with workflow orchestration tools such as Step Functions, Airflow, or custom AWS-based solutions. Soft Skills: Strong communication, problem-solving, and collaboration skills. Able to lead discussions on architecture and best practices.

Note: Candidates are required to attend Phone/video calls and in-person interviews. After the Selection, the candidate (He/She) should undergo all background checks on Education and Experience.

Application: Please email your resume to greeshmac@petadata.co. After carefully reviewing your experience and skills, one of our HR team members will contact you on the next steps.