Data Conversion Tester

Client : State of Mississippi 

Work Type : Onsite

Location : Jackson, Mississippi

Minimum Relevant Experience :  4 Years

Minimum Relevant Experience : Minimum Relevant Experience : 4 Years(Data Conversion Testing) and 5 Years in testing of the eligibility determination, benefit issuance(SNAP,TANF,CC,CSE)

Compensation : Based on Experience

Duration : Long Term

eSystems Inc. is a fast-growing Systems Integrator based in Princeton, New Jersey. We provide strategic IT solutions and services with primary practice areas in Java and Microsoft centric e-Business solutions, ERP solutions, Enterprise Application Integration, Data Warehousing and Business Intelligence solutions.

Our clients include Fortune 500 corporations, government agencies, small and mid-sized local businesses, and non-profit organizations.

As an equal opportunity employer, eSystems complies with all applicable laws, rules and regulations preventing discrimination against job applicants based on: race, ethnicity, religious beliefs, gender, gender identity, age, veteran status, marital status, physical challenges, or any other relevant factor

THE JD and the required skillset are below. Please make sure that the suitable candidate has at least 90% of the skillset mentioned

• Validate converted data from legacy systems to new platforms, ensuring accuracy, completeness, and compliance with program rules.
• Compare source and target data to confirm correct mapping, transformation, and loading.
• Verify that converted data supports correct eligibility determination, benefit issuance, and case workflows for SNAP, TANF, CC, and CSE.
• Test data scenarios involving household composition, income, deductions, sanctions, time limits, co‑payments, provider data, enforcement actions, and payment histories.
• Validate notices, correspondence, and system‑generated documents using converted data.

• Develop detailed data conversion test cases, test scripts, and validation checklists.
• Create and execute SQL queries or other data validation tools to verify data accuracy.
• Perform functional and end‑to‑end testing using converted data to ensure system behavior aligns with program rules.
• Document defects with clear evidence and collaborate with data migration and development teams to resolve issues.

• Validate program‑specific data elements, including:
  • SNAP – income, deductions, household composition, benefit allotments.
  • TANF – work participation, time limits, benefit amounts, sanctions.
  • Child Care Assistance (CC) – provider information, co‑payments, eligibility periods.
  • Child Support Enforcement (CSE) – case establishment, enforcement actions, payment records.
• Ensure data integrity across interfaces, batch processes, and downstream systems.
• Confirm compliance with federal and state regulations and policy updates.

• Work closely with data migration teams to understand mapping documents, transformation rules, and conversion logic.
• Participate in data validation workshops, requirement walkthroughs, and defect triage meetings.
• Provide clear, detailed documentation for audits, certification, and implementation readiness.

• 4–6 years of QA or data validation experience, preferably in HHS eligibility and benefits systems.
• Hands‑on experience with data conversion testing for SNAP, TANF, CC, and/or CSE programs.
• Strong understanding of eligibility determination, benefit issuance, and case management workflows.
• Experience validating data mapping, transformation rules, and ETL processes.
• Proficiency with SQL or similar tools for data validation.
• Experience with test management and defect tracking tools (e.g., JIRA, Azure DevOps, ALM).
• Strong analytical, documentation, and problem‑solving skills.

• Experience with large‑scale system modernization or integrated eligibility system migrations.
• Familiarity with legacy HHS systems and common data structures.
• Experience testing APIs, batch jobs, and data interfaces.
• Prior work with state HHS agencies or multi‑vendor project environments.

• Strong attention to detail and commitment to data accuracy.
• Ability to work independently and collaboratively across technical and business teams.
• Clear communication skills, especially when explaining data issues and validation results.
• Adaptability in fast‑paced, high‑visibility project environments.