Databricks Architect with AI Experience: 15+ Years Location: Ahmedabad Position: FTE / Contract Contract Duration: 1 Year Budget for contract: ₹2.2 LPM Budget for FTE : Upto 31 LPA Role Overview We are looking for an experienced Databricks Data Architect to lead the architecture and implementation of enterprise-scale data platforms using Databricks Lakehouse. The role requires strong expertise in data architecture, modern data engineering, dimensional modeling, cloud platforms and AI-enabled data solutions. The candidate will act as the technical owner of the data platform, driving architecture decisions, engineering standards, performance optimization and technical governance.

Key Responsibilities Design and lead enterprise-scale Databricks Lakehouse architectures covering ingestion, transformation, storage, governance and analytics. Define scalable and secure data architecture standards, reusable frameworks and engineering best practices. Design and implement ETL/ELT pipelines using PySpark, Spark SQL and Databricks.

Architect

Bronze, Silver and Gold data layers using Delta Lake and Medallion Architecture. Design and optimize Delta Lake storage, partitioning, performance and data lifecycle strategies.

Implement Databricks

Workflows / Lakeflow for orchestration and automation. Establish data quality, validation, reconciliation and monitoring frameworks. Design enterprise data models using Dimensional Modeling, Star Schema, Fact and Dimension tables and SCD. Define business metrics, KPI layers, semantic models and Metric Views for analytics. Lead migration and modernization of legacy data warehouse platforms to Databricks. Drive CI/CD and DevOps practices across data engineering projects. Provide technical leadership, conduct architecture and code reviews, and mentor data engineering teams. Troubleshoot complex architecture and performance issues and guide teams toward scalable solutions. Work directly with client architects,



business stakeholders and technical teams to translate requirements into robust solutions. Define target-state architecture, technical roadmaps and governance across multiple workstreams. AI & Contemporary Data Capabilities Experience integrating AI/ML capabilities with modern data platforms. Understanding of AI-ready data architecture and preparation of curated datasets for advanced analytics. Ability to design scalable data foundations supporting AI and Generative AI use cases. Exposure to modern Databricks AI capabilities is an advantage.

Required Technical Skills

Databricks & Data Engineering Databricks Lakehouse Architecture Delta Lake Unity Catalog Databricks SQL Databricks Workflows / Lakeflow PySpark & Spark SQL ETL / ELT Batch & Incremental Processing Performance Tuning & Optimization Data Architecture & Modeling Enterprise Data Architecture Dimensional Data Modeling Star Schema Fact & Dimension Modeling Slowly Changing Dimensions (SCD) Metric Views & Analytical Data Modeling Data Quality & Governance Cloud & Tools Azure Databricks ADLS Gen2 Azure Data Factory Batch & Event-based Ingestion Python & SQL Git and CI/CD Good to Have Data Warehouse Modernization / Legacy EDW Migration Medallion Architecture and Data Mesh Data Governance, Metadata Management and Data Cataloging Power BI, Tableau or Looker Experience with AI/ML and Generative AI data solutions Candidate Profile Strong experience owning end-to-end Databricks architecture and implementation. Proven ability to define target-state architecture and technical roadmaps. Strong leadership and mentoring capabilities. Excellent communication and stakeholder-management skills. Ability to drive architecture decisions across multiple teams and workstreams. Strong focus on scalability, security, performance and long-term maintainability.

Mandatory Skills Data

Architecture, Databricks Interested candidates can share their CV at: [email protected]

Pay: Up to ₹3,100,000.00 per year

Work Location: In person

📌 Databricks Architect with AI (Ahmedabad)
🏢 Snehal
📍 Ahmedabad