AWS Data Engineer

System One
Birmingham, AL, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Business Analytics Applications Big Data Continuous Integration Information Engineering Extract Transform Load (ETL) Database Queries Python (Programming Language) Performance Tuning SQL Databases Data Processing
+8 more
Sql Optimization Generative AI Information Technology Deployment Automation AWS Glue AWS Data Analytics Data Pipelines Amazon Redshift

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

Requirements

  • 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.

Education Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical field.

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