Data Engineer

Design, develop, and support scalable ETL pipelines, data integration processes, and database solutions, with strong focus on Oracle environments.

Perform data profiling, data quality validation, reconciliation, and source-to-target validation.

Develop and optimize SQL, data models, and database solutions for enterprise data environments.

Collaborate within Agile/SCRUM teams to deliver end-to-end data engineering solutions across the Prime Services domain.

Troubleshoot data, ETL, and production issues to ensure system reliability and performance.

Support cloud-based data solutions and implement modern data engineering technologies and best practices.

Create technical documentation, data mappings, and architecture/solution diagrams.

Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or related field.

Strong hands-on Oracle experience, including SQL/PLSQL, database design, and performance optimization.

Strong experience with advanced SQL, data modeling, and ETL/data integration.

Hands-on experience with data quality, reconciliation, profiling, and validation.

Experience with Informatica, SnapLogic, Kafka, or comparable ETL/integration technologies.

Proficiency in Python and/or Java.

Experience with AWS, Azure, or Google Cloud Platform and cloud-based data solutions.

Experience with end-to-end data integration and production support.

Preferred: Snowflake, Kubernetes, CI/CD (Jenkins, Artifactory, uDeploy), API development, AI/ML, or BI/Analytics experience.