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# Data Engineer II

- **Company:** Everforth Apex
- **Location:** Cincinnati, OH, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Systems, IBM InfoSphere DataStage, Oracle (Applications), Scrum Methodology, SQL Databases, Snowflake, Information Technology, Data Pipelines
- **Published:** November 4, 2026
- **Apply:** https://www.dice.com/job-detail/78623e8c-c4fd-4ec8-aa7b-c021be26c4be

## About the Role

Education: A bachelor's degree in computer science, information technology, data engineering, or a related field is preferred.

Experience: A minimum of three years of data engineering experience with a strong background in developing ETL processes and data pipelines.

Technical Skills: Proficiency in SQL and data modeling techniques, along with experience working with modern data technologies.

Preferred Qualifications

 * Experience with Snowflake and dbt.
 * Experience with IBM DataStage.
 * Domain knowledge within financial services or treasury systems.
 * Familiarity with Oracle, OFSA, QRM, or Oracle Funds Transfer Pricing.
 * Ability to work independently and manage tasks without extensive direction.

## Description

Our organization is seeking a Data Engineer II to support a technology team focused on data modernization. The selected candidate will help modernize legacy data pipelines, support existing production infrastructure, and collaborate directly with business partners to translate complex business problems into viable technical solutions. This position offers an opportunity to work within a collaborative, fast-paced environment and drive significant impact through modern data engineering practices., * Modernize legacy ETL and data pipelines to support business modernization goals.

 * Develop robust data models and pipeline solutions.
 * Support business-critical applications and address operational pipeline needs.
 * Collaborate with business partners to gather and clarify requirements.
 * Translate ambiguous business challenges into structured technical requirements.
 * Provide production support for existing data workflows.
 * Operate effectively within two-week Agile sprints.
 * Work collaboratively with other engineering team members to ensure alignment and quality.