100% Remote – SAS Data Engineer C2C jobs

Tech Mirrors

Florida

Remote

USD 110.000 - 170.000

Vollzeit

14 Tage+

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Zusammenfassung

Tech Mirrors is seeking an experienced SAS Data Engineer for a remote, long-term contract. The role centers on migrating and validating SAS logic, with strong emphasis on Python/PySpark automation and data reconciliation to ensure functional equivalence between source and target platforms.

You will analyze SAS programs, create QA scenarios, and collaborate with cross-functional teams and clients to resolve discrepancies, driving high-quality migration outcomes in a SaaS/enterprise data

Qualifikationen

  • 7+ years of hands-on SAS programming experience including DATA Step, PROC SQL, Macros, Datasets and Job Analysis.
  • Strong Python and PySpark experience for data processing, automation, validation and reconciliation.
  • QA experience in SAS migration, ETL validation, source-to-target testing and data quality checks.
  • Strong SQL skills for querying, profiling, reconciliation and validation across large datasets.
  • Excellent communication skills to work with technical teams, business users, QA teams and client stakeholders.

Aufgaben

  • Analyze SAS programs, jobs, datasets and business logic to support migration and validation.
  • Create and execute QA test scenarios for SAS migration and modernization projects.
  • Validate source-to-target outputs for data accuracy, completeness, reconciliation and functional equivalency.
  • Use Python and PySpark for automation, data comparison, profiling and validation.
  • Perform defect analysis, root-cause investigation and prepare validation reports/status updates.
  • Collaborate with data engineering, QA, business and client stakeholders to resolve discrepancies.

Kenntnisse

SAS
Python
PySpark
SQL
QA testing
Data migration
ETL

Tools

Databricks
Snowflake

Jobbeschreibung

Role: SAS Data Engineer

Location: Remote

Duration: Long Term contract

Mode of Interview: MS Teams

Must Have
  • SAS (7+ years of hands-on experience)
Secondary Skill
  • Primary: Python, PySpark
  • Secondary: Databricks, Snowflake (Optional) - We can have 1-2 resources with these skills
Role Overview

We are looking for experienced SAS Migration Engineers / Data Engineers with 7+ years of hands-on SAS experience and strong Python/PySpark skills to support SAS migration, modernization, validation, and QA activities.

The role focuses on analyzing SAS logic, validating migrated outputs, performing data reconciliation, and ensuring accuracy, completeness, and functional equivalency across source and target platforms.

Key Responsibilities
  • Analyze SAS programs, jobs, datasets, and business logic to support migration and validation.
  • Create and execute QA test scenarios for SAS migration and modernization projects.
  • Validate source-to-target outputs for data accuracy, completeness, reconciliation, and functional equivalency.
  • Use Python and PySpark for automation, data comparison, profiling, and validation.
  • Perform defect analysis, root-cause investigation, and prepare validation reports/status updates.
  • Collaborate with data engineering, QA, business, and client stakeholders to resolve discrepancies.
Required Skills
  • 7+ years of strong hands-on SAS programming experience, including DATA Step, PROC SQL, Macros, Datasets, and Job Analysis.
  • Strong hands-on experience in Python and PySpark for data processing, automation, validation, and reconciliation.
  • Strong QA experience in SAS migration, ETL validation, source-to-target testing, and data quality checks.
  • Strong SQL skills for querying, profiling, reconciliation, and validation across large datasets.
  • Excellent communication skills to work with technical teams, business users, QA teams, and client stakeholders.
Preferred Skills
  • SAS migration or modernization experience, especially migration from SAS to Python/PySpark based platforms.
  • Optional exposure to Databricks or Snowflake; 1-2 resources with these skills would be beneficial.
  • Experience with ETL workflow validation, batch process testing, reporting validation, and QA sign-off documentation.
  • Exposure to Agile delivery, test management tools, and defect tracking processes.
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