Location: Onsite. Cincinnati, OH
Must Have Skills:
- At least 5 years of experience working with relational and non-relational databases (e.g., SQL, Snowflake, DB2, MongoDB).
- Minimum 5 years of experience analyzing legacy codebases (SQL, DataStage, SAS)
- Python, Java, or J2EE
- Python, Java, or J2EE.
Qualifications:
Bachelors degree in Computer Science, Information Systems, or related field; or equivalent work
experience.
Minimum 5 years of experience analyzing legacy codebases (SQL, DataStage, SAS) and documenting
business logic.
At least 5 years of experience working with relational and non-relational databases (e.g., SQL,
Snowflake, DB2, MongoDB).
3+ years of experience developing backend solutions using programming languages such as Python,
Java, or J2EE.
3-5 years of experience building and maintaining data pipelines using tools like DataStage, dbt, and
other ETL frameworks.
Minimum 5 years of experience in business analysis, including stakeholder engagement and
translating requirements into technical solutions.
Excellent communication and interpersonal skills; able to work effectively with technical and
non-technical teams.
2+ years of experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
Experience in financial services or banking, especially in commercial lending, underwriting, or
regulatory reporting, is a strong plus.
Prior Agile experience is a strong plus.
Ability to work independently and manage multiple priorities in a fast-paced environment.
Summary:
The contractor will be responsible for deep analysis of legacy systems? including SQL, DataStage, and SAS code? To identify key data attributes, document current data usage, and assess downstream impacts.
Primary Responsibilities:
Analyze existing SQL, DataStage, and SAS code to extract business logic and identify critical data
elements.
Create detailed inventories of current data usage across reporting and operational systems.
Assess the impact of data migration on downstream processes, reports, and regulatory requirements.
Design, construct, install, test, and maintain scalable data management systems aligned with
migration goals.
Collaborate with business stakeholders to gather requirements and translate them into actionable
engineering tasks.
Integrate modern data management and software engineering technologies into existing data
ecosystems.
Develop and optimize data pipelines for mining, modeling, and production.
Create custom software components and analytics applications tailored to commercial lending and risk
reporting.
Recommend improvements to enhance data reliability, quality, and performance.
Implement and maintain disaster recovery procedures.
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