Data Integration Lead

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.