We are looking for an experienced Data Architect to lead enterprise-scale data platform modernization initiatives across Databricks, AWS, and Snowflake ecosystems. The ideal candidate will architect scalable, secure, and AI-ready data platforms supporting analytics, machine learning, and enterprise intelligence.

Key Responsibilities :

- Lead enterprise-scale implementation of modern data warehouse and lakehouse platforms on Databricks and Snowflake environments.

- Design and implement Medallion (Bronze/Silver/Gold) architecture and scalable enterprise data models.

- Establish and enforce enterprise data modeling standards including Dimensional Modeling, Data Vault, and Lakehouse patterns.

- Define and implement data governance frameworks covering cataloging, lineage, stewardship, metadata management, and compliance using Atlan.

- Build and implement CI/CD pipelines for infrastructure provisioning, automated deployments, and data platform management.

- Design architectures supporting AI/ML and Generative AI workloads, including feature stores, vector storage, and secure data access frameworks.

- Build scalable ingestion frameworks supporting batch, streaming, and CDC pipelines.

- Architect secure, high-performance integration layers for analytics, BI, reporting, and AI consumption.

- Develop target-state architecture blueprints and enforce enterprise standards, governance, and platform best practices.

- Collaborate with engineering, analytics, and data science teams to ensure platform scalability and alignment.

- Engage with clients as a trusted advisor, driving data strategy, roadmap planning, architecture consulting, and business growth opportunities.

Ideal Candidate Profile :

- 8+ years of experience in Data Architecture / Data Engineering with strong exposure to enterprise-scale data modernization programs.

- Minimum 3+ years of deep hands-on experience in Databricks-based lakehouse architecture on AWS and large-scale platform implementations.

- Strong expertise across the Databricks ecosystem, including Delta Lake, Databricks SQL, Unity Catalog, Delta Live Tables (DLT), MLflow, performance optimization, and platform security.

- Strong hands-on experience with AWS data services including S3, Glue, EMR, Lambda, Redshift, Athena, Lake Formation, and DMS.

- Proven expertise in Medallion Architecture, scalable data modeling (Dimensional/Data Vault), and

enterprise lakehouse platforms supporting batch and real-time processing.

- Hands-on experience building scalable ingestion frameworks using Kafka, Kinesis, Spark, or similar technologies.

- Strong experience implementing CI/CD pipelines, Infrastructure as Code (IaC), automated deployments, and environment management for data platforms.

- Hands-on exposure enabling platforms for AI/ML and Generative AI use cases, including feature stores, vector storage, and secure data access patterns.

- Experience with orchestration tools such as Apache Airflow or MWAA and designing integration layers for analytics, BI, and AI workloads.

- Experience from Product Companies will be preferred.

- AWS / Databricks / Snowflake certifications are an advantage.

- Exposure to Snowflake environments, MDM, data quality frameworks, and enterprise metadata tools is preferred.