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Sap Successfactors Data Conversion Analyst Jobs

Phoenix Staff

Data Conversion Analyst

Phoenix, AZ

$45 - $58/hr

Data Conversion Analyst Location: Hybrid Compensation: $45- $58/hr hourly contract, $95,000 - $115,000 conversion salary Employment Type: Contract-to-Hire We are seeking a Data Conversion Analyst to ...

Grant Street Group

OR · On-site

$70K - $120K/yr

If the following describes you, you're a perfect fit for the data conversion analyst role at Grant Street Group. You want to work with a team of awesome project managers, business analysts ...

Grant Street Group

Data Conversion Analyst

$70K - $120K/yr

If the following describes you, you're a perfect fit for the data conversion analyst role at Grant Street Group. You want to work with a team of awesome project managers, business analysts ...

Navtech, Inc.

Workday Data Conversion Lead

Yonkers, NY · On-site

... HCM, SAP SuccessFactors, etc. The lead will also be responsible for presenting the design ... Excellent problem-solving skills, with the ability to analyze complex data conversion issues and ...

Leeds Professional Resources

Be Seen First

SAP Payroll Consultant- ADP (WFN) implementations

Boca Raton, FL · On-site

$50 - $90/hr

... SAP SuccessFactors Responsibilities * Lead and support ADP Workforce Now (WFN) implementation ... Support payroll data conversion, validation, reconciliation, and reporting activities. * Leverage ...

Palnar

Sr.SAP Success factors consultant@ Remote Role

$64.50 - $88/hr

Experience with various SuccessFactors modules, including Employee Central, Recruiting, Onboarding ... data conversion. * Strong understanding of HR processes, including recruitment, onboarding ...

Advanced Micro Devices, Inc

Sr. HRIS Analyst (SAP)

Austin, TX · Hybrid

$89K - $114K/yr

Configuration SAP SuccessFactors Data Model (field level configuration) as well as leveraging MDF ... Strong analytical, problem-solving, and solution design skills * Ability to interpret HR systems ...

Definian

Workday Data Conversion Lead

Chicago, IL

Mentor and guide junior conversion analysts and support team members across concurrent workstreams ... Experience migrating data from legacy ERP and HRIS platforms such as Oracle EBS, SAP, PeopleSoft ...

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All JobsSap Successfactors Data Conversion Analyst Jobs

Sap Successfactors Data Conversion Analyst information

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$93

How much do sap successfactors data conversion analyst jobs pay per hour?

As of Jun 16, 2026, the average hourly pay for sap successfactors data conversion analyst in the United States is $58.39, according to ZipRecruiter salary data. Most workers in this role earn between $41.59 and $72.60 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a SAP SuccessFactors Data Conversion Analyst, and why are they important?

To thrive as a SAP SuccessFactors Data Conversion Analyst, you need expertise in HR data structures, data mapping, and a solid understanding of SAP SuccessFactors modules, typically backed by experience in HRIS implementations. Proficiency with ETL tools, SAP Data Services, Excel, and familiarity with SuccessFactors data templates or certifications is highly valued. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for translating business requirements and ensuring data accuracy. These competencies ensure accurate data migration, minimize errors, and support seamless HR system integrations for organizational success.

What are Sap Successfactors Data Conversion Analysts?

SAP SuccessFactors Data Conversion Analysts are professionals responsible for migrating and transforming data from legacy HR systems into SAP SuccessFactors, a cloud-based human capital management solution. Their main tasks include analyzing data requirements, mapping data fields, cleansing and validating data, and ensuring data accuracy during the migration process. They collaborate closely with business stakeholders, technical teams, and project managers to ensure a successful transition to the new system. Strong knowledge of data structures, ETL (Extract, Transform, Load) processes, and SAP SuccessFactors modules is essential for this role.

What are some common challenges faced by a SAP SuccessFactors Data Conversion Analyst during implementation projects?

A SAP SuccessFactors Data Conversion Analyst often encounters challenges such as mapping legacy HR data to the new SuccessFactors data model, ensuring data accuracy and completeness, and handling discrepancies or missing information from legacy systems. Collaborating closely with both technical teams and HR stakeholders is crucial to understand data requirements and resolve issues efficiently. Additionally, tight project timelines and coordinating multiple test cycles require strong organizational and communication skills to ensure successful data migration and minimal disruption to HR operations.
Infographic showing various Sap Successfactors Data Conversion Analyst job openings in the United States as of June 2026, with employment types broken down into 2% Locum Tenens, 93% Full Time, and 5% Temporary. Highlights an 81% Physical, 8% Hybrid, and 11% Remote job distribution, with an average salary of $121,445 per year, or $58.4 per hour.
Data Conversion Analyst

Data Conversion Analyst

Phoenix Staff

Phoenix, AZ

$45 - $58/hr

Full-time, Contractor

Posted 14 days ago

Job description

Data Conversion Analyst

Location: Hybrid

Compensation: $45- $58/hr hourly contract, $95,000 - $115,000 conversion salary

Employment Type: Contract-to-Hire


We are seeking a Data Conversion Analyst to support large-scale data migration and modernization initiatives. This role is focused on understanding, analyzing, cleansing, mapping, validating, and reconciling data as it moves from legacy systems into modern platforms.

The ideal candidate has hands-on experience with complex data conversion projects and understands that successful migrations are iterative. They know how to identify data quality issues, determine appropriate cleansing strategies, develop mapping rules, validate conversion results, and collaborate with both business and technical teams to ensure data accuracy.


Responsibilities

  • Analyze source system data to identify anomalies, inconsistencies, and data quality issues.
  • Develop and maintain detailed source-to-target and target-to-source mappings.
  • Identify data gaps and determine appropriate remediation strategies.
  • Support data cleansing, transformation, and validation activities throughout the conversion lifecycle.
  • Perform reconciliation between legacy and target systems to ensure data accuracy and completeness.
  • Collaborate with Business Analysts, SMEs, architects, and developers to define transformation rules and business logic.
  • Document mapping decisions, transformation rules, validation results, and conversion processes.
  • Participate in multiple conversion cycles and support continuous refinement of conversion results.
  • Validate migrated data and support business sign-off activities.

Required Qualifications

  • 3+ years of experience supporting data migration, conversion, integration, or data quality initiatives.
  • Experience developing source-to-target and target-to-source data mappings.
  • Strong SQL Server experience (required).
  • Strong understanding of relational database concepts, normalization, and database structures.
  • Experience identifying and resolving data quality issues and "dirty data."
  • Experience performing reconciliation and validation activities during migrations.
  • Excellent documentation skills.
  • Strong communication skills and ability to work with both business and technical stakeholders.


Preferred Qualifications

  • Experience supporting large enterprise data conversion projects.
  • Experience with Microsoft data technologies including Azure SQL, Azure Data Lake, or Microsoft Fabric.
  • Experience working with data governance, lineage, and auditability requirements.


What We're Looking For

Successful candidates should be able to clearly explain:

  • How they approach dirty data and data quality issues.
  • How they determine where and how data should be cleansed.
  • How they perform reconciliation between old and new systems.
  • Their experience creating and validating data mappings.
  • The specific role they played in prior conversion projects.
  • The size and complexity of conversion efforts they have supported.