About this role
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. Requirements Minimum 10 years of experience in Data & Analytics Architecture with proven leadership in large-scale enterprise data modernization initiatives Strong understanding of batch, streaming, real-time, and near real-time data architectures Proven experience implementing enterprise Data Governance frameworks and tool Hands-on experience enabling AI/ML and Generative AI data pipelines. Deep expertise in data domains including Data Warehousing, Data Modeling (Dimensional, Data Vault), MDM, Data Quality, Metadata Management, and Data Catalog implementation Advanced Databricks experience including architecture design, optimization, and security; including hands-on experience with Delta Lake, Databricks SQL, Unity Catalog, Delta Live Tables, MLflow and integration with cloud services (AWS/Azure) Strong hands-on experience with AWS data ecosystem (S3, Glue, EMR, Lambda, Redshift, Lake Formation, Athena, DMS, etc.) Experience with real-time/streaming technologies (Kafka, Kinesis, or similar) Familiarity with orchestration tools such as Apache Airflow or MWAA Experience implementing CI/CD pipelines for data platforms AWS, Databricks and/or Snowflake certifications preferred Note: Given the urgency of the role, we are currently prioritizing candidates who can join immediately or within 2 weeks.
