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Solution Architect – Azure Databricks

Job in Bengaluru, 560001, Bangalore, Karnataka, India
Listing for: Tata Consultancy Services
Full Time position
Listed on 2026-06-13
Job specializations:
  • IT/Tech
    Data Engineering, Cloud Computing, AI Engineer (Applied/Software), Data Science Manager
Job Description & How to Apply Below
Location: Bengaluru

Greetings From TCS!!!

TCS presents an Excellent opportunity for  Solution Architect – Azure Databricks
Desired Experience Range:  8 to 10+ Years
Location of Requirement:  Bangalore
Required Skill:  Azure cloud services, Databricks Unified Analytics Platform, Big data, Data science

Technical/Functional

Skills:

The  Azure Databricks Solution Architect  is responsible for designing and implementing data solutions leveraging  Azure cloud services  and the  Databricks Unified Analytics Platform . The role focuses on big data, data engineering, data science, and machine learning workloads, working closely with stakeholders and leading technical discussions to deliver scalable, secure, and robust solutions.
Deep understanding of  Databricks Unified Analytics Platform :
Apache Spark, Delta Lake, MLflow
Strong hands-on experience with  Azure Cloud services  and their  integration with Databricks .
Strong programming skills in  SQL ,  Python , and  Java .

Experience with  data warehousing  and  ETL  processes.
Experience in designing and implementing  edge computing solutions  end-to-end

Responsibility of / Expectations from the Role:
Solution Design & Architecture
Design and implement  end-to-end data solutions  using Azure services and Databricks for big data, analytics, and ML use cases.
Lead  architecture and design discussions  with product, engineering, and business stakeholders.

Data Pipelines & Platforms
Design and build  scalable, reliable data pipelines  for ingestion, transformation, storage, and retrieval.
Consult on  big data architectures  and validate integrations with other cloud services, on-prem systems, and third-party applications.

Machine Learning Pipelines
Implement  ML pipelines  in Databricks using  MLflow  for experiment tracking, model management, and deployment.
Integrate ML workflows with other Azure services to support model training, validation, and serving.

Note:

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Warm Regards,
Shalini C – HR-TAG,
Tata Consultancy Services, India.
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