We are hiring a Data Architect to lead a strategic enterprise data modernization initiative for
platform
using Medallion architecture
AWS Databricks. The role will define target-state architecture,
establish
enterprise data governance frameworks, implement CI/CD best practices for data platforms, and build GenAI-ready data foundations that enable advanced analytics, machine learning, and secure enterprise data access.

You will
be responsible for
architecting scalable cloud-native data ecosystems, designing governed data models, and enabling real-time and batch data processing capabilities. This role requires deep ownership of architecture standards, platform performance, and cross-functional alignment across engineering, analytics, and data science teams to ensure consistent, secure, and high-performance data consumption across enterprise use cases.

Location
- Mumbai/
Bangalore
/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities -

• 
  Lead enterprise-scale
  implementation of
  data warehouse
  data
  platforms
  on Databricks
  and
  Snowflake environments.
• 
  Design and implement Medallion (Bronze/Silver/Gold) architecture and scalable enterprise data models.
• 
  Establish data modeling standards (dimensional, data vault,
  lakehouse
  patterns) and ensure best practices across projects
• 
  Establish enterprise data governance frameworks including cataloging, lineage, stewardship, and compliance using Atlan.
• 
  Define and implement CI/CD pipelines for infrastructure and data platform deployments
• 
  Design data architectures that support AI/ML and Generative AI workloads including vector storage, feature layers, and secure access patterns.
• 
  Build scalable ingestion frameworks supporting batch, streaming, and CDC pipelines.
• 
  Architect secure, high-performance data integration layers for analytics, BI, and AI consumption.
• 
  Develop target-state architecture blueprints and enforce data standards, governance, and best practices across teams.
• 
  Collaborate with engineering, analytics, and data science teams to ensure platform alignment and scalability.
• 
  Engage with clients as a trusted advisor, driving data strategy, roadmap definition, and
  identifying
  opportunities for expansion.