Technical Architect

Mphasis · Pune

Source and collection record

Last observed by our collector: 8 October 2026 at 11:49 pm IST. This is not a manual review or a confirmation from the employer.

Employer requisition: 117997-10-1

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Collected role description

Senior Databricks Engineer – SAS Modernisation & Migration Role Summary Looking for a strong Databricks Engineer who understands how SAS platforms work and can modernise SAS workloads into Databricks. The role covers discovery, migration, validation, optimisation and production deployment of SAS workloads onto Databricks. The individual should be capable of understanding SAS business logic and rebuilding it efficiently using Databricks, PySpark and modern data engineering practices. Core Skills (Must Have) Databricks (Primary Skill) Azure Databricks / Databricks Lakehouse PySpark Spark SQL Python Delta Lake Unity Catalog Databricks Workflows Medallion Architecture (Bronze/Silver/Gold) Performance tuning and optimisation CI/CD and Git-based development Production support and troubleshooting SAS (Strong Working Knowledge) Base SAS SAS DATA Step PROC SQL SAS Macros SAS Enterprise Guide  SAS Grid / SAS Viya  Batch scheduling and job dependencies  SAS datasets, libraries and file processing  Understanding of SAS business logic and data lineage   Key Responsibilities  SAS Discovery & Assessment   Analyse SAS estate and identify dependencies, business logic and migration complexity.  Inventory SAS jobs, datasets, macros and interfaces.  Classify workloads for retire, refactor, re-engineer or migrate.   SAS to Databricks Migration  Convert SAS code to PySpark/Spark SQL. Re-engineer legacy SAS processing into scalable Databricks solutions. Develop Delta Lake pipelines and Databricks workflows. Support automated conversion and manual remediation where required. Validation & Reconciliation Compare SAS and Databricks outputs. Build automated reconciliation frameworks. Perform record count, aggregation and business logic validation. Support UAT and business sign-off. Architecture & Engineering Design Databricks Lakehouse solutions. Implement governance using Unity Catalog. Optimise performance, scalability and cost. Support Dev, Test and Production deployments. Experience Required 8+ years in Data Engineering / Analytics. 4+ years hands-on Databricks experience. 3+ years working with SAS environments. Previous experience in SAS to Databricks , SAS to PySpark or similar data-platform modernisation programs. Experience in large enterprise environments involving migration, reconciliation and production cutovers.

Collected experience requirement

7 - 10 Years