Technical Architect

Mphasis; Maharashtra; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Mphasis is seeking a strong Databricks Engineer who can modernise SAS workloads into Databricks. The role covers discovery, migration, validation, optimisation and production deployment of SAS workloads onto Databricks, using PySpark and modern data engineering practices.

Responsibilities include SAS discovery, migration, architecture, and production support, with emphasis on converting SAS code to scalable Databricks solutions and ensuring data lineage and governance.

Qualifications

• 8+ years in Data Engineering / Analytics.
• 4+ years hands-on Databricks experience.
• 3+ years working with SAS environments.

Responsibilities

• SAS Discovery & Assessment: analyse SAS estate, dependencies and migration complexity.
• SAS to Databricks Migration: convert SAS code to PySpark/Spark SQL and re-engineer processing.
• Architecture & Engineering: design Databricks Lakehouse, implement Unity Catalog governance and optimise performance.

Skills

PySpark

Spark SQL

Python

Unity Catalog

Databricks Workflows

Medallion Architecture

Performance tuning

CI/CD

Production support

Base SAS

SAS DATA Step

PROC SQL

SAS Macros

SAS Grid / SAS Viya

Batch scheduling

SAS datasets

Data lineage

Job description

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)

• PySpark


• Spark SQL


• Python


• 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 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.


• 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.