About the role
Job Title: SAS Data Engineer
Location: Remote, US
Work Arrangement: Remote
Employment Type: Contract
Duration: 28 months
Domain: Information Technology | Data Engineering & Modernization
Pay Rate: $45.89/hr W2 | $55.40/hr C2C
Application Deadline: August 29, 2026
SKILLS REQUIRED
Primary (Must-Have):
• 7+ years of hands-on SAS programming (DATA step | PROC SQL | Macros | Datasets | Job Analysis)
• Strong proficiency in Python and PySpark (Data Processing | Automation | Validation | Reconciliation)
• Comprehensive QA and ETL Data Migration Validation (Source-to-Target Testing | Data Quality Checks)
• Advanced SQL skills (Data Profiling | Complex Querying | Large Dataset Reconciliation)
Secondary (Good to Have):
• Direct SAS to Python/PySpark platform modernization and migration experience
• Exposure to modern cloud data platforms (Databricks | Snowflake)
• ETL workflow validation, batch process testing, reporting validation, and QA sign-off documentation
• Working knowledge of Agile methodologies, test management frameworks, and defect tracking systems
POSITION OVERVIEW
The SAS Data Engineer plays a pivotal role in driving data modernization initiatives by supporting SAS-to-cloud migration, validation, and QA activities. Reporting to the Data Engineering Lead, this individual will analyze complex legacy SAS business logic, automate target platform validations, and perform end-to-end data reconciliation using Python and PySpark. The role directly addresses the critical business need for ensuring complete functional equivalency, data accuracy, and seamless architectural transition across source and target platforms.
ROLES & RESPONSIBILITIES
• Analyze legacy SAS programs, job schedules, datasets, and business logic to map out migration requirements and technical dependencies.
• Validate source-to-target outputs using Python and PySpark to execute automated data comparison, profiling, and full-scale reconciliation.
• Design, build, and execute robust QA test scenarios, ETL validation scripts, and source-to-target test cases for data quality assurance.
• Perform complex defect triage, root-cause investigation on data discrepancies, and compile clear validation reports for key stakeholders.
• Collaborate daily with cross-functional data engineering, QA, business, and executive client teams to resolve data issues and secure QA sign-off.
BENEFITS
Medical | Dental | Vision | 401(k)
EEOC Compliance:
We are an equal opportunity employer, and all qualified applicants will receive consideration for employment.
DISCLAIMER
AI Usage Policy: Pacer Group uses AI to assist in screening applications. Final hiring decisions are made by human recruiters based on qualifications and experience.
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