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Job Description
Job Description Insight Global is hiring a Lead AWS Data Engineer to support one of their largest financial industry clients. In this role, you will serve as the technical lead responsible for architecting scalable AWS data solutions and overseeing the implementation and management of end-to-end data pipelines, including ingestion, storage, transformation, and analytics using AWS services. You will mentor and guide data engineers, conduct code reviews, and promote best practices in cloud data engineering and architecture. You'll also collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to translate requirements into scalable, maintainable solutions. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.
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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements
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 a lead engineer role
Extensive hands-on experience with AWS data services (Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, Athena, RDS, API Gateway, etc.)
Programming proficiency in Python and SQL
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 Experience with DevOps practices, CI/CD pipelines, and infrastructure-as-code tools (e.g., CloudFormation, Terraform)
AWS Solutions Architect or AWS Data Engineer certification(s)
Experience with shell scripting and Scala is a plus
Experience with real-time streaming technologies
Knowledge of data governance, compliance, and security best practices
Familiarity with Lakehouse architecture and modern data platforms