Junior Data Management and Quantitative Analyst

Hybrid 4 days onsite in Pittsburgh, PA

Our client seeks a detail-focused data management analyst to support a legacy middle-office environment for a single client. The role centers on BAU processing, security master setups and maintenance, and rigorous data validation within older Eagle versions. Success will require accuracy, basic SQL use for data review, and frequent client communication via Teams while operating within strict timelines.

We can facilitate w2 and corp-to-corp consultants. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $25.00 to $28.00/hr. w2

Responsibilities

• Work from a shared inbox to action BAU requests with timely, accurate responses.
• Perform security setups, ongoing security maintenance, and data validation in a legacy Eagle environment.
• Monitor and process items in the validation queue and follow internal recycle processes.
• Execute manual updates and track new security setups to ensure correct downstream data flow.
• Use SQL to review and validate data using provided queries.
• Conduct root cause analysis for data errors and recommend remediation steps.
• Prepare ad-hoc reports and ensure accuracy and quality of deliverables.
• Adhere to data quality standards, controls, and issue management procedures.
• Engage with the client via Teams with professional, clear communication.
• Manage workload in a deadline-driven environment and escalate issues as needed.

• Ability to learn complex financial data quickly and apply business rules.
• Strong attention to detail with a high standard for accuracy.
• Basic SQL familiarity for querying and data review.
• Comfort working in older or unfamiliar systems and navigating new software.
• Organization, documentation, and written and oral communication skills.
• Experience implementing or measuring data quality and controls (preferred).
• Experience with issue management systems (preferred).
• Familiarity with logical data models (preferred).
• Knowledge of structuring data environments and big data applications (preferred).
• Strong knowledge of Excel (preferred).
• Banking, product/financial services, auditing, or compliance experience (preferred).

• Bachelor’s degree in Finance or Accounting preferred; other fields considered with training.