About the role

Databricks Solution Architect / Data Architect

Company:	EXL Analytics
Location:	Pune \| Bangalore \| Noida \| Gurgaon

Job Summary

EXL Analytics is looking for an experienced Databricks Solution Architect / Data Architect to lead the design and implementation of enterprise-scale data platforms on Azure. The ideal candidate will have strong expertise in Azure Databricks, Lakehouse architecture, Delta Lake, and enterprise data engineering, with the ability to define scalable architecture, optimize platform performance, and drive best practices across data engineering teams.

Key Responsibilities

Design and architect enterprise-scale data platforms using Azure Databricks and Lakehouse architecture.
Build scalable ETL/ELT pipelines using PySpark, SQL, Delta Lake, Databricks Workflows, Auto Loader, and Delta Live Tables.
Define architecture standards, data models, reusable frameworks, CI/CD processes, and engineering best practices.
Implement data governance, security, and lineage using Unity Catalog, RBAC, and Azure Purview.
Optimize Spark workloads, cluster performance, and overall platform cost and scalability.
Collaborate with business stakeholders, product teams, and engineering teams to deliver scalable analytics and AI-ready solutions.
Mentor development teams, conduct architecture reviews, and provide technical leadership throughout project delivery.

Required Skills

10–15 years of experience in Data Engineering, Data Architecture, or Cloud Data Platforms.
5+ years of hands-on experience with Azure Databricks.
Strong expertise in Databricks, PySpark, Python, SQL, Delta Lake, Auto Loader, Delta Live Tables (DLT), and Databricks Workflows.
Experience with Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure DevOps, Azure Key Vault, and CI/CD implementation.
Strong understanding of Lakehouse, Medallion Architecture, Data Modeling, Data Governance, Unity Catalog, and Azure Purview.
Experience in Spark performance tuning, workload optimization, and cost optimization.
Excellent communication, stakeholder management, and technical leadership skills.

Preferred

Experience in the Insurance domain and exposure to AI/ML and advanced analytics platforms.