Job Description
Responsibilities:
Analyze SAS programs to understand sources, dependencies, data flow.
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 JD
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:
4+ years of experience in SAS Base.
Exposure to Python, PySpark Development and SQL knowledge 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.
Proficient in Python and Scala scripting for data manipulation and analysis.
Excellent communication, collaboration, and problem-solving skills.
Strong leadership and team-building abilities.
Analyze SAS programs to understand sources, dependencies, data flow.
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 JD
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:
4+ years of experience in SAS Base.
Exposure to Python, PySpark Development and SQL knowledge 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.
Proficient in Python and Scala scripting for data manipulation and analysis.
Excellent communication, collaboration, and problem-solving skills.
Strong leadership and team-building abilities.
💡 Quick Summary
Seeking a career-building opportunity? The Data Integration Engineer position is now open for candidates interested in the Software Developer Jobs sector. This role in Mumbai offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Software Developer Jobs is a plus.
