What are the responsibilities and job description for the Senior Data Lake Engineer position at PETADATA?
Position: Senior Data Lake Engineer
Location: Dallas, TX(Remote)
Work Type: C2C
Experience: 15 Years
PETADATA 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.
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.
Roles & Responsibilities
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
We offer a professional work environment and provide every opportunity for growth in the Information technology world.
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.
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
Location: Dallas, TX(Remote)
Work Type: C2C
Experience: 15 Years
PETADATA 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.
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.
Roles & 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.
- 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.
- AWS Certifications (e.g., AWS Certified Data Analytics, AWS Certified Solutions Architect)
- Experience with Athena, Redshift, or other analytics services in the AWS ecosystem
- Exposure to DevOps practices and tools like Terraform, CloudFormation, or CDK
- Familiarity with data cataloging and metadata management tools
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
We offer a professional work environment and provide every opportunity for growth in the Information technology world.
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.
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