{"id":2767474,"url":"https://alion.io/job/doublu-sas-migration-databricks-modernization-engineer","title":"SAS Migration & Databricks Modernization Engineer","company":{"id":3812749,"name":"DoublU","domain":"godoublu.com","url":"https://alion.io/company/doublu","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India","Bengaluru, India","Mumbai, India","Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":20000,"max_usd":41000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":71},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Linux","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SAS","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-27T14:33:04Z","employer_posted_date":null,"last_verified_at":"2026-09-27T14:33:04Z","board_verified":false,"closed_at":null,"days_open":28,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":28},"description":"Role Overview : \n\nWe are looking for experienced SAS Migration & Databricks Modernization Engineers to support a large-scale analytics transformation program involving SAS-to-Altair SLC migration and future Databricks modernization initiatives.\n\nThe ideal candidate should have strong expertise in SAS, Linux and analytics workload migration, along with working knowledge of Databricks, Python, SQL and modern data engineering practices.\n\nPrimary Skills : \n\n- SAS Migration\n\n- SAS Base\n\n- SAS Macros\n\n- Data Step Programming\n\n- SAS Procedures\n\n- SAS Batch Processing\n\n- SAS Enterprise Guide\n\n- SAS Reporting\n\n- Databricks\n\n- Spark / PySpark\n\n- SQL\n\n- Python\n\n- Linux\n\n- Shell Scripting\n\n- ETL/ELT\n\n- Data Warehousing\n\n- Lakehouse Architecture\n\nKey Responsibilities : \n\nSAS Workload Assessment & Migration : \n\n- Assess and inventory SAS applications, jobs, macros, libraries, reports and dependencies.\n\n- Analyze SAS workloads for compatibility with Altair SLC.\n\n- Identify migration risks, remediation requirements and modernization opportunities.\n\n- Migrate SAS batch jobs, scheduled processes and analytics workloads to Altair SLC.\n\n- Configure and manage SAS-compatible execution environments on Linux.\n\n- Support migration of SAS metadata, libraries, data connections and reporting processes.\n\n- Validate SAS procedures, data steps, macros, formats and ODS outputs.\n\nDatabricks Modernization & Data Engineering : \n\n- Participate in Databricks modernization initiatives on AWS.\n\n- Support migration of legacy SAS workloads to Databricks, Python or PySpark.\n\n- Develop and optimize data pipelines using Databricks, Spark, SQL and Python.\n\n- Collaborate with architecture teams to evaluate workloads for cloud-native execution.\n\n- Design scalable ETL/ELT processes using Lakehouse principles.\n\nData Validation & Testing : \n\n- Develop and execute migration test strategies.\n\n- Perform source-to-target validation and reconciliation.\n\n- Use data validation and automation frameworks.\n\n- Validate data parity, report accuracy and business rule consistency.\n\n- Support UAT and business certification activities.\n\nPerformance Optimization : \n\n- Benchmark migrated workloads against existing SAS environments.\n\n- Tune Altair SLC runtime performance.\n\n- Optimize Linux infrastructure, storage and network utilization.\n\n- Improve job execution efficiency and resource consumption.\n\n- Implement monitoring and operational dashboards.\n\nDevOps & Automation : \n\n- Develop migration automation utilities and deployment pipelines.\n\n- Configure CI/CD pipelines for analytics applications.\n\n- Utilize Infrastructure-as-Code practices where applicable.\n\n- Manage source control and releases using Git-based workflows.\n\n- Automate operational and support activities.\n\nSkills\nSAS, Databricks, Python, PySpark, SQL, Data Migration, Data Engineering, Linux, ETL, Data 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