Experinece - 10+ Years
Job Summary: 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, API Gateway, 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.
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