Responsibilities: • Experience implementing data integration workflows using SAS tools such as SAS DI Studio. • Sanitize SAS programs in preparation for conversion. • Optimize SAS programs in preparation for conversion. • Incorporate changes in accelerator to ensure generated code aligns to required standards • Utilize accelerator to convert SAS programs to PySpark programs. • Demonstrate and document code lineage. • Unit Test generated PySpark programs • Incorporate feedback from PySpark EAP integration, SIT and parity-check. • Prepare for deployment. • Experience analyzing and understanding SAS processes and statistical methods to identify trends, patterns, and correlations. • Proficiency in SAS programming and tools • Developing and maintaining SAS programs for automation and analysis. • Proven expertise in Spark, SQL, including data pipeline and notebook development. • Troubleshooting user issues and resolving system errors. • Managing SAS jobs and schedules and working with SAS metadata. • Migration of SAS Jobs, Stored Procedures, SAS Programs, Reports, SAS Datasets, Excel, and CSV files from Development to Production Environment. • Ensure compliance with data security, privacy regulations, and organizational standards. Qualifications: • 6+ years of experience in SAS and must have experience in Base SAS and SAS EG (Enterprise Guild) with exposure to Python and PySpark is good to have. • Experience in SAS Mainframe (Good to have). • Strong understanding of data architecture, data modelling, and ETL/ELT processes. • Experience with big data processing and distributed computing systems like Spark and Kafka. • Proficient in Python and Scala scripting for data manipulation and analysis. • Excellent communication, collaboration, and problem-solving skills. • Strong leadership and team-building abilities

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