SAS Migration+DataBricks

Position: SAS Migration+Databricks

Experience: 8-12 Years

Location: Pune / Mumbai / Chennai / Bangalore

Detailed Job Description:

SAS Migration & Databricks Modernization Engineer Position Title: SAS Migration & Databricks Modernization Engineer Department: Sentinel Job Category: Data & Analytics Employment Type: Contract / Full-Time (Based on Program Demand) Hiring Need: Additional resources to support for Sentinel project SAS migration and future Databricks modernization initiatives.

Position Overview: 

             As the SAS Migration program expands, we are seeking experienced professionals who can support both the immediate SAS-to-Altair SLC migration initiative and the longer-term cloud modernization roadmap involving Databricks. The ideal candidate will possess strong expertise in SAS, Linux, and analytics workload migration, along with working knowledge of Databricks, Python, and modern data engineering practices. The role requires close collaboration with business users, data engineers, platform teams, and analytics stakeholders to ensure seamless migration, validation, modernization, and operational stability. This position offers an opportunity to participate in a large-scale analytics transformation program focused on reducing SAS dependency while enabling future adoption of cloud-native analytics platforms.

Key Responsibilities 

SAS Workload Assessment & Migration

• Assess and inventory SAS applications, jobs, macros, libraries, reports, and dependencies. 
• Analyze SAS workloads for compatibility with Altair SLC. 
• Identify migration risks, remediation requirements, and modernization opportunities. 
• Migrate SAS batch jobs, scheduled processes, and analytics workloads to Altair SLC. 
• Configure and manage SAS-compatible execution environments on Linux platforms. 
• Support migration of SAS metadata, libraries, data connections, and reporting processes.

 • Validate compatibility of SAS procedures, data steps, macros, formats, and ODS outputs.

Databricks Modernization & Data Engineering 

• Participate in modernization initiatives involving Databricks on AWS. 
• Support migration of legacy SAS data processing workloads to Databricks, Python, or PySpark where applicable. 
• Develop and optimize data pipelines using Databricks, Spark, SQL, and Python. 
• Collaborate with architecture teams to evaluate workload suitability for cloud-native execution. • Design scalable ELT/ETL processes using Lakehouse principles.

Data Validation & Testing 

• Develop and execute migration test strategies. 
• Perform source-to-target validation and reconciliation. 
• Leverage internal data validation accelerators and automation frameworks. 
• Validate data parity, report accuracy, and business rule consistency. 
• Support user acceptance testing (UAT) and business certification activities.

 Performance Optimization 

• Benchmark migrated workloads against existing SAS environments. 
• Tune Altair SLC runtime performance. 
• Optimize Linux infrastructure, storage, and network utilization. 
• Improve job execution efficiency and resource consumption. 
• Implement monitoring, ing, and operational dashboards. 

 DevOps & Automation 

• Develop migration automation utilities and deployment pipelines. 
• Configure CI/CD pipelines for analytics applications. 
• Utilize Infrastructure-as-Code practices where applicable. 
• Manage source control and release processes using Git-based workflows. 
• Automate operational and support activities.

 Cutover & Production Support 

• Execute migration cutover activities and deployment planning. 
• Create operational runbooks and recovery procedures. 
• Support hypercare and production stabilization efforts. 
• Investigate and resolve migration-related defects and performance issues. 
• Provide ongoing support and optimization recommendations.

Required Qualifications:

SAS Expertise 

• 5-8+ years of hands-on SAS experience. 
• Strong knowledge of: o SAS Base o SAS Macros o Data Step Programming o SAS Procedures o SAS Batch Processing o SAS Enterprise Guide o SAS Reporting Databricks & Modern Data Platforms 
• Experience with Databricks, Spark, PySpark, SQL, or cloud data platforms. 
• Understanding of data warehousing and analytics modernization.

 • Familiarity with Lakehouse architecture concepts. 

Linux & Infrastructure 

• Strong Linux administration experience: o RHEL o Ubuntu • Shell scripting and automation experience. 
• Experience managing batch processing workloads. Database & Data Integration 
• Experience with: o SQL Server o Oracle o Teradata o PostgreSQL o Hadoop-based platforms 
• Strong SQL skills. DevOps • Git • CI/CD Pipelines • Terraform • Ansible • Monitoring and Observability Tools 

 Preferred Qualifications 

• Experience with Altair SLC or other SAS-compatible runtimes.