À propos
The SAS Analytics Modernization Engineer contributes to the migration of SAS-based analytical environments into modern cloud platforms. This role is responsible for translating, validating, and optimizing SAS code, data pipelines, and statistical models so they perform reliably outside of legacy systems. You'll play a key role in preserving business-critical analytics while helping move them into a more scalable, cloud-based future.
The Impact You'll Have
This role exists to solve a very real problem: organizations depend on years of SAS-based analytics, but those environments are no longer built for how modern data platforms operate. You'll help bridge that gap-ensuring that reporting, modeling, and analytical workflows built in SAS continue to function accurately as they are migrated and modernized.
You'll directly support the transition of SAS-driven reporting, customer analytics, and statistical models into cloud environments like GCP. That includes rewriting and refactoring SAS code, validating outputs against legacy systems, and identifying where logic, data structures, or performance need to be improved. Your work will protect business continuity while enabling more flexible, scalable analytics.
You'll also work across data engineering, analytics, and data science teams to make sure SAS-based workflows integrate cleanly into broader data ecosystems. This is not just a lift-and-shift role-you'll help shape how legacy analytics evolves into something more durable.
What you'll do:
Migrate and Refactor SAS Workflows
Translate and migrate SAS 9.4 and SAS Viya code into cloud-based environments, including GCP Refactor SAS programs, macros, and data steps to align with modern data architectures and performance expectations Rebuild SAS-driven data pipelines and analytical workflows in ways that are maintainable and scalable Validate SAS Outputs with Precision
Compare outputs between legacy SAS environments and cloud-based implementations to ensure exact or explainable parity Perform regression testing across datasets, reporting outputs, and statistical models originally developed in SAS Identify discrepancies in logic, joins, aggregations, or transformations and resolve them systematically Support SAS-Based Models and Analytics
Migrate and validate SAS-based statistical models and analytical processes to ensure consistent performance post-migration Work with data science and analytics teams to preserve model behavior while adapting to new environments Ensure that SAS-driven business logic remains intact and interpretable after migration Strengthen Data Integrity and Testing
Develop repeatable validation frameworks for SAS data pipelines and analytical outputs Implement automated checks and monitoring to detect data or logic issues early Improve reliability and transparency of SAS-based workflows as they transition to cloud platforms Collaborate to Modernize SAS Ecosystems
Partner with data engineering, analytics, and platform teams to integrate SAS workflows into broader cloud data environments Work with business stakeholders to maintain continuity of reporting and analytics during migration Document SAS logic, transformations, and migration decisions to support long-term maintainability What you'll need:
Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field Strong hands-on experience with SAS 9.4 and/or SAS Viya, including data steps, PROC SQL, macros, and batch processing Experience migrating or modernizing SAS-based analytical environments Strong SQL skills and understanding of how SAS interacts with relational data systems Experience validating SAS outputs, including datasets, reporting, and statistical model results Deep understanding of data structures, ETL processes, and analytical workflows within SAS environments Experience troubleshooting discrepancies in SAS code, data transformations, and analytical outputs Familiarity with cloud data platforms such as GCP, AWS, or Azure Ability to work across data engineering, analytics, and business teams to support migration and continuity Strong attention to detail and commitment to data accuracy, reproducibility, and documentation Ability to clearly explain SAS logic, transformations, and validation results to both technical and non-technical stakeholders Future-Ready Skills (Nice to Have):
Experience translating SAS workflows into Python, SQL, or cloud-native data processing frameworks Familiarity with GCP tools such as BigQuery, Cloud Composer, and Vertex AI in SAS migration contexts Experience building automated validation or testing frameworks for SAS-to-cloud migrations Exposure to CRM, customer analytics, or marketing data ecosystems built on SAS Experience optimizing SAS workloads for performance before or during migration Background in consulting, agency, or enterprise environments with large legacy SAS footprints Experience in integrated marketing, digital agency, marketing services, or consulting environments preferred.
Benefits
We believe great work happens when people have the support and flexibility they need to thrive. Our benefits include medical, dental, and vision coverage, a 401(k) retirement plan, paid holidays, and Flexible Time Off (FTO) so you can take time away to recharge when you need it. We also offer additional programs focused on wellness, financial security, and professional growth.
We are an equal opportunity employer
We believe that Innovative ideas and solutions start with unique perspectives. That's why we're committed to providing every employee a workplace that's free of discrimination and intolerance. We're proud to be an equal opportunity employer and actively search for like-minded people to join our team.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform job functions, and to receive benefits and privileges of employment. Please contact us to request accommodation.
Compétences linguistiques
- English
Avis aux utilisateurs
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