Databricks Architect

Alike Thoughts; Ahmedabad District; Hybrid; INR 3,000,000 - 5,400,000; Full time

Job summary

Alike Thoughts is seeking an experienced Databricks Data Architect to lead the design and implementation of enterprise-scale data platforms on Databricks. You will provide architectural guidance, establish best practices, mentor teams, and ensure scalable, high-performance solutions across ingestion, transformation, storage, and governance layers.

You will own the Databricks implementation lifecycle, drive architectural governance, and lead data modeling and Delta Lake strategies while

Qualifications

• Experience in design architecture and implementation of enterprise-scale data platforms on Databricks.
• Strong expertise in modern data engineering practices, dimensional data modeling, and Databricks Lakehouse architecture.
• Provide architectural guidance, best practices, mentoring development teams, and ensuring successful delivery of scalable data solutions.
• Define end-to-end data architecture including ingestion, transformation, storage, governance, and consumption layers.
• Oversee CICD and DevOps practices for data engineering projects.

Responsibilities

• Design and implement enterprise-scale data platforms using the Databricks Lakehouse architecture.
• Define end-to-end data architecture including ingestion transformation storage governance and consumption layers.
• Establish architectural standards framework guidelines coding best practices and reusable design patterns.
• Lead technical decisions related to scalability performance optimization reliability and security.
• Conduct architecture reviews and provide recommendations to project teams.
• Design and build scalable ETL/ELT pipelines using PySpark on Databricks.
• Architect and implement Bronze Silver Gold data transformation frameworks.
• Design and manage Delta Lake based storage architecture including partitioning optimization and data lifecycle management.
• Implement Databricks Lakeflow pipelines for data orchestration and automation.
• Define data quality validation reconciliation and monitoring frameworks.
• Oversee CICD and DevOps practices for data engineering projects.
• Design and implement enterprise data models using Dimensional Modeling techniques.
• Develop Star Schemas, Fact Tables, Dimension Tables and conformed dimensions.
• Define business metrics KPI layers and semantic models.
• Architect and implement Metric Views and curated Gold datasets for reporting and analytics.
• Work closely with business stakeholders to translate requirements into scalable analytical models.
• Provide technical leadership and mentorship to data engineers and developers.
• Perform code reviews and ensure adherence to architecture standards.
• Troubleshoot complex technical issues and guide teams in solution design.
• Drive adoption of modern data engineering and cloud-native best practices.

Skills

Databricks Lakehouse Architecture

Databricks Workflows Lakeflow

Delta Lake

Unity Catalog

Databricks SQL

Performance Tuning

PySpark

Spark SQL

ETL/ELT Design

Data Pipeline Development

Data Quality Frameworks

Batch and Incremental Processing

Data Modeling

Dimensional Modeling

Star Schema

SCD

Metric View Design

Analytical Data Modeling

Azure Databricks

ADLS Gen2

Azure Data Factory

Event-driven Ingestion

Data Governance & Security

Python

SQL

Git

CI/CD Frameworks

Job description

Role Overview

We are seeking an experienced Databricks Data Architect to lead the design architecture and implementation of enterprisescale data platforms on Databricks The ideal candidate should possess strong expertise in modern data engineering practices dimensional data modeling and Databricks Lakehouse architecture

The candidate will act as the technical owner of the data platform providing architectural guidance establishing best practices mentoring development teams and ensuring successful delivery of scalable highperformance data solutions

Key Responsibilities

Architecture Solution Design

• Design and implement enterprisescale data platforms using the Databricks Lakehouse architecture
• Define endtoend data architecture including ingestion transformation storage governance and consumption layers
• Establish architectural standards framework guidelines coding best practices and reusable design patterns
• Lead technical decisions related to scalability performance optimization reliability and security
• Conduct architecture reviews and provide recommendations to project teams

Data Engineering Databricks Implementation

• Design and build scalable ETLELT pipelines using PySpark on Databricks
• Architect and implement Bronze Silver Gold data transformation frameworks
• Design and manage Delta Lake based storage architecture including partitioning optimization and data lifecycle management
• Implement Databricks Lakeflow pipelines for data orchestration and automation
• Define data quality validation reconciliation and monitoring frameworks
• Oversee CICD and DevOps practices for data engineering projects

Data Modeling Analytics Enablement

• Design and implement enterprise data models using Dimensional Modeling techniques
• Develop Star Schemas Fact Tables Dimension Tables and conformed dimensions
• Define business metrics KPI layers and semantic models
• Architect and implement Metric Views and curated Gold datasets for reporting and analytics
• Work closely with business stakeholders to translate requirements into scalable analytical models

Technical Leadership

• Provide technical leadership and mentorship to data engineers and developers
• Perform code reviews and ensure adherence to architecture standards
• Troubleshoot complex technical issues and guide teams in solution design
• Support estimation solution proposals and technical governance activities
• Drive adoption of modern data engineering and cloudnative best practices

Required Technical Skills

Core Databricks Skills

• Databricks Lakehouse Architecture
• Databricks Workflows Lakeflow
• Delta Lake
• Unity Catalog
• Databricks SQL
• Performance Tuning Optimization

Data Engineering

• PySpark
• Spark SQL
• ETL ELT Design
• Data Pipeline Development
• Data Quality Frameworks
• Batch and Incremental Processing
• Data Modeling
• Dimensional Data Modeling
• Star Schema Design
• Fact Dimension Modeling
• Slowly Changing Dimensions SCD
• Metric View Design
• Analytical Data Modeling

Cloud Integration

• Azure Databricks preferred
• ADLS Gen2
• Azure Data Factory ADF
• Eventbased and Batch Ingestion Patterns
• Data Governance and Security

Programming

• Python
• SQL
• Git
• CICD Frameworks

Desired Skills

• Data Warehouse Modernization experience
• Experience migrating legacy EDW solutions to Databricks
• Exposure to Data Mesh and Medallion Architecture
• Knowledge of Data Governance Metadata Management and Data Cataloging
• Experience supporting BI platforms such as Power BI Tableau or Looker

Leadership Expectations

The candidate should be capable of

• Owning the complete Databricks implementation lifecycle
• Defining targetstate architecture and roadmap
• Reviewing designs and code produced by team members
• Guiding developers on PySpark optimization and data modeling best practices
• Driving technical discussions with client architects and business stakeholders
• Ensuring scalability maintainability and longterm sustainability of the platform
• Providing architectural governance across multiple workstreams

Skills

Mandatory Skills : Data Architecture, Databricks