Data Engineer

Job Title: AWS Data Engineer Duration: 7 months (Possibility of extension) Location: Hybrid (Newark, NJ)/ W2 Only Job Summary: We are seeking an experienced AWS 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. 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.