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 & Modern 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 contemporary 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

Pay: Up to ₹2,800,000.00 per year

Work Location: In person

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