AWS Data Engineer

AWS Lead Data Engineer

We are seeking an experienced AWS Lead Data Engineer to join our Data Engineering team. As a technical leader, you will be responsible for architecting, implementing, and managing scalable data solutions on AWS. You will provide technical guidance to a team of data engineers, collaborate with cross-functional partners, and ensure best practices in cloud data engineering. Candidate would be required to work from NJ office as part of this role.

Key Responsibilities:

• Lead the design, development, and optimization of large-scale, reliable, and secure data pipelines and data lake architecture on AWS.
• Architect and implement end-to-end data solutions, including data ingestion, storage, transformation, and analytics using AWS services (Glue, Redshift, S3, Lambda, EMR, Kinesis, Athena, RDS, etc.).
• Mentor and guide a team of data engineers, conducting code reviews and fostering best practices in data engineering and cloud architecture.
• Collaborate with data scientists, analysts, and business stakeholders to translate requirements into scalable and maintainable solutions.
• Oversee migration of data from legacy systems to AWS-based data lakes and data warehouses.
• Develop and enforce standards for data quality, security, and governance.
• Drive the adoption of DevOps, CI/CD, and infrastructure-as-code practices within the data engineering team.
• Ensure solutions are cost-effective, performant, and aligned with enterprise data strategy.
• Stay current with advancements in AWS technologies and data engineering trends and evaluate new tools and frameworks for potential adoption.
• Troubleshoot complex data issues and provide technical leadership in problem resolution.

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 7+ years of experience in data engineering, with at least 3 years in technical leadership or lead engineer role.
• Extensive hands-on experience with AWS data services (Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, Athena, RDS, etc.).
• Proficient in programming languages such as Python and SQL; experience with Shell scripting and Scala is a plus.
• Strong experience designing, implementing, and managing data lakes, data warehouses, and data ingestion pipelines on AWS.
• Proven experience with ETL/ELT processes, data modeling, and big data frameworks.
• Demonstrated ability to lead, mentor, and coach engineers in a collaborative team environment.
• Experience with DevOps practices, CI/CD pipelines, and infrastructure-as-code tools (e.g., CloudFormation, Terraform).
• Excellent problem-solving, communication, and organizational skills.

Preferred Qualifications:

• AWS Solutions Architect or AWS Data Engineer certification.
• Experience with real-time streaming technologies.
• Knowledge of data governance, compliance, and security best practices.
• Familiarity with Lakehouse architecture and modern data platforms.