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Mid-level, popular data role in a metro market with broad skill requirements increases applicant competition.
Core data engineering skills are transferable, though financial domain experience provides advantage.
Explicit 3+ years and mandatory Python, SQL, AWS, Glue, Kafka creates moderate filtering.
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Design, build, and maintain scalable ETL pipelines and backend data workflows using Python, SQL, and AWS technologies.
Develop and optimize data processing solutions on AWS (Glue, EMR, Lambda, S3) supporting analytics, reporting, and downstream applications.
Implement CI/CD pipelines to automate build, test, and deployment processes, ensuring code quality and reliability.
Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.
Minimum 3 years of experience in software development focused on backend or data engineering.
Proficiency in Python, strong SQL skills, and hands-on experience with AWS services including Glue, EMR, Lambda, S3, and Kafka.
Experience with CI/CD pipelines and tools for automated build, test, and deployment processes.
Experienced in building and maintaining ETL/data pipelines in cloud environments with strong AWS and data engineering expertise.
Able to collaborate across teams to translate business requirements into technical solutions and participate in technical discussions.
Operates with strong software development discipline including version control, automated testing, and troubleshooting complex data issues.