Technology

AWS Data Engineer

System OneLafayette, LA🇺🇸United States

Why this role stands out

This role offers a fantastic opportunity to advance your career in cloud-based data engineering within a reputable financial services company, focusing on innovative AWS technologies and complex analytics solutions. You'll thrive here if you enjoy independent problem-solving, collaborating with diverse teams, and driving impactful projects from concept to completion. Apply today to shape the future of enterprise risk analytics and potentially explore Generative AI applications.

Quick overview

SeniorityMid Senior

Work modeOn Site

LocationLafayette, LA, United States

SQLAWSETLGenerative AIPythonRedshift

Job description

Job Title: AWS Data Engineer
Duration: Full Time / Permanent Position
Location: Birmingham, AL, Knoxville, TN, Columbia, SC or Lafayette, LA.
Work Mode: 5 Days Onsite
Systemone is seeking a Senior AWS Data Engineer to support the development, enhancement, and maintenance of enterprise risk analytics applications within a large-scale financial services environment.
This role will focus on building and improving cloud-based data pipelines and analytics solutions using AWS technologies, with particular emphasis on Amazon Redshift, AWS Glue, Python, and SQL. The successful candidate will work with complex business and technical requirements, develop reliable data processing solutions, and contribute to automation and CI/CD practices.
Your Future Duties and Responsibilities
As a senior level resource, this individual should be comfortable working independently, troubleshooting complex data issues, collaborating with cross functional teams, and helping drive solutions from requirements through implementation and production support. Exposure to Generative AI and opportunities to apply AI driven automation within data engineering workflows is also valuable.
Required Qualifications to Be Successful in This Role

5+ years of hands-on experience with AWS based data engineering.
Experience with Amazon Redshift, including data processing and performance optimization.
Hands-on experience developing ETL/data pipelines using AWS Glue.
Strong Python development skills for data processing and automation.
Advanced SQL skills, including complex queries and large data sets.
Experience with CI/CD pipelines and automated deployment practices.
Experience developing and maintaining enterprise scale data and analytics applications.
Understanding of data quality, troubleshooting, performance, and production support.
Exposure to Generative AI (GenAI) and AI enabled automation use cases.
Ability to work through complex requirements with limited oversight.
Strong communication and collaboration skills.
Financial services, enterprise risk, or risk analytics experience is preferred.