Databricks Developer / Data Architect

Posted 7 Days Ago
Be an Early Applicant
Pune, Mahārāshtra, IND
Hybrid
Senior level
Information Technology • Database • Consulting
The Role
Design and implement Databricks Lakehouse architectures and Medallion pipelines; build and optimize scalable ETL/ELT using PySpark/Spark SQL; integrate multi-source data (RDBMS/NoSQL/cloud); manage Databricks workspaces, governance, CI/CD, and platform integrations across Azure and AWS to enable analytics and high-performance data solutions.
Summary Generated by Built In

Job Description: Databricks Developer / Data Architect

Position Title

Databricks Developer / Data Architect

Location

Hybrid/ Remote

Employment Type

Full-Time / Contract

Job Summary

We are seeking an experienced Databricks Developer / Data Architect to design, implement, and optimize modern data platforms and ETL pipelines using Databricks and cloud-native technologies. The ideal candidate will have strong expertise in data architecture, Lakehouse implementation, Medallion Architecture, and scalable ETL development across Azure and AWS environments.

The role involves setting up Databricks workspaces, configuring data integrations and Lakehouse Federation, building enterprise-grade ETL workflows, and enabling high-performance analytics solutions.

 

Key Responsibilities

Data Architecture & Modeling

  • Design and implement scalable enterprise data architectures using Databricks Lakehouse platform 
  • Configure and manage Databricks workspaces, clusters, access controls, and governance 
  • Implement Medallion Architecture (Bronze, Silver, Gold layers) for data processing and analytics 
  • Set up and manage Lakehouse Federation and data connectors for multi-source integration 
  • Develop logical and physical data models for structured and semi-structured datasets 
  • Ensure data quality, security, scalability, and performance optimization 

ETL Development

  • Develop and maintain scalable ETL/ELT pipelines using PySpark, Spark SQL, and Databricks workflows 
  • Build reusable data ingestion frameworks for batch and streaming workloads 
  • Optimize Spark jobs for performance, cost efficiency, and reliability 
  • Integrate data from relational and NoSQL databases, cloud platforms, and external systems 
  • Automate deployment and monitoring of ETL workflows 

Cloud & Platform Engineering

  • Work with Azure and AWS cloud services to deploy and manage data solutions 
  • Configure integrations with Snowflake, Postgres, MongoDB, DynamoDB, Cloudera, and Domino Server 
  • Support CI/CD, infrastructure automation, and environment management 
  • Collaborate with cross-functional teams including Data Scientists, Analysts, and Business stakeholders 
 

Required Skills & Qualifications

  • 5+ years of experience in Data Engineering / Data Architecture 
  • Strong hands-on experience with Databricks platform 
  • Expertise in: 
    • Python 
    • Apache Spark 
    • PySpark 
    • SQL 
  • Strong understanding of: 
    • Lakehouse Architecture 
    • Medallion Architecture 
    • Data Modeling 
    • ETL/ELT Design Patterns 
  • Experience with cloud platforms: 
    • Microsoft Azure 
    • AWS 
  • Experience integrating with: 
    • PostgreSQL 
    • DynamoDB 
    • MongoDB 
    • Snowflake 
    • Cloudera 
    • Domino Server 
  • Knowledge of performance tuning and optimization in Spark/Databricks 
  • Experience with version control and DevOps practices 
 

Preferred Qualifications

  • Databricks Certification(s) 
  • Experience with Delta Lake and Unity Catalog 
  • Familiarity with streaming frameworks and real-time data processing 
  • Knowledge of data governance and security best practices 
  • Experience in Agile/Scrum delivery models 
 

Technical Stack

  • Databricks 
  • Python 
  • Spark / PySpark 
  • SQL 
  • Azure 
  • AWS 
  • Snowflake 
  • PostgreSQL 
  • MongoDB 
  • DynamoDB 
  • Cloudera 
  • Domino Server 
 

Soft Skills

  • Strong analytical and problem-solving abilities 
  • Excellent communication and stakeholder management skills 
  • Ability to work independently and collaboratively in fast-paced environments 
  • Strong documentation and solution design capabilities 
 

Nice-to-Have

  • Experience with Terraform or Infrastructure as Code 
  • Exposure to ML/data science platforms 
  • Experience with orchestration tools such as Airflow or Azure Data Factory 
Responsibilities

Job Description: Databricks Developer / Data Architect

Position Title

Databricks Developer / Data Architect

Location

Hybrid/ Remote

Employment Type

Full-Time / Contract

Job Summary

We are seeking an experienced Databricks Developer / Data Architect to design, implement, and optimize modern data platforms and ETL pipelines using Databricks and cloud-native technologies. The ideal candidate will have strong expertise in data architecture, Lakehouse implementation, Medallion Architecture, and scalable ETL development across Azure and AWS environments.

The role involves setting up Databricks workspaces, configuring data integrations and Lakehouse Federation, building enterprise-grade ETL workflows, and enabling high-performance analytics solutions.

 

Key Responsibilities

Data Architecture & Modeling

  • Design and implement scalable enterprise data architectures using Databricks Lakehouse platform 
  • Configure and manage Databricks workspaces, clusters, access controls, and governance 
  • Implement Medallion Architecture (Bronze, Silver, Gold layers) for data processing and analytics 
  • Set up and manage Lakehouse Federation and data connectors for multi-source integration 
  • Develop logical and physical data models for structured and semi-structured datasets 
  • Ensure data quality, security, scalability, and performance optimization 

ETL Development

  • Develop and maintain scalable ETL/ELT pipelines using PySpark, Spark SQL, and Databricks workflows 
  • Build reusable data ingestion frameworks for batch and streaming workloads 
  • Optimize Spark jobs for performance, cost efficiency, and reliability 
  • Integrate data from relational and NoSQL databases, cloud platforms, and external systems 
  • Automate deployment and monitoring of ETL workflows 

Cloud & Platform Engineering

  • Work with Azure and AWS cloud services to deploy and manage data solutions 
  • Configure integrations with Snowflake, Postgres, MongoDB, DynamoDB, Cloudera, and Domino Server 
  • Support CI/CD, infrastructure automation, and environment management 
  • Collaborate with cross-functional teams including Data Scientists, Analysts, and Business stakeholders 
 

Required Skills & Qualifications

  • 5+ years of experience in Data Engineering / Data Architecture 
  • Strong hands-on experience with Databricks platform 
  • Expertise in: 
    • Python 
    • Apache Spark 
    • PySpark 
    • SQL 
  • Strong understanding of: 
    • Lakehouse Architecture 
    • Medallion Architecture 
    • Data Modeling 
    • ETL/ELT Design Patterns 
  • Experience with cloud platforms: 
    • Microsoft Azure 
    • AWS 
  • Experience integrating with: 
    • PostgreSQL 
    • DynamoDB 
    • MongoDB 
    • Snowflake 
    • Cloudera 
    • Domino Server 
  • Knowledge of performance tuning and optimization in Spark/Databricks 
  • Experience with version control and DevOps practices 
 

Preferred Qualifications

  • Databricks Certification(s) 
  • Experience with Delta Lake and Unity Catalog 
  • Familiarity with streaming frameworks and real-time data processing 
  • Knowledge of data governance and security best practices 
  • Experience in Agile/Scrum delivery models 
 

Technical Stack

  • Databricks 
  • Python 
  • Spark / PySpark 
  • SQL 
  • Azure 
  • AWS 
  • Snowflake 
  • PostgreSQL 
  • MongoDB 
  • DynamoDB 
  • Cloudera 
  • Domino Server 
 

Soft Skills

  • Strong analytical and problem-solving abilities 
  • Excellent communication and stakeholder management skills 
  • Ability to work independently and collaboratively in fast-paced environments 
  • Strong documentation and solution design capabilities 
 

Nice-to-Have

  • Experience with Terraform or Infrastructure as Code 
  • Exposure to ML/data science platforms 
  • Experience with orchestration tools such as Airflow or Azure Data Factory 
Qualifications

Preferred Qualifications

  • Databricks Certification(s) 
  • Experience with Delta Lake and Unity Catalog 
  • Familiarity with streaming frameworks and real-time data processing 
  • Knowledge of data governance and security best practices 
  • Experience in Agile/Scrum delivery models 
 

Technical Stack

  • Databricks 
  • Python 
  • Spark / PySpark 
  • SQL 
  • Azure 
  • AWS 
  • Snowflake 
  • PostgreSQL 
  • MongoDB 
  • DynamoDB 
  • Cloudera 
  • Domino Server 
 

Soft Skills

  • Strong analytical and problem-solving abilities 
  • Excellent communication and stakeholder management skills 
  • Ability to work independently and collaboratively in fast-paced environments 
  • Strong documentation and solution design capabilities 
 

Nice-to-Have

  • Experience with Terraform or Infrastructure as Code 
  • Exposure to ML/data science platforms 
  • Experience with orchestration tools such as Airflow or Azure Data Factory 

Skills Required

  • 5+ years of experience in Data Engineering / Data Architecture
  • Hands-on experience with Databricks platform
  • Python
  • Apache Spark
  • PySpark
  • SQL
  • Knowledge of Lakehouse Architecture
  • Knowledge of Medallion Architecture
  • Data Modeling
  • ETL/ELT Design Patterns
  • Experience with Microsoft Azure
  • Experience with AWS
  • Integration experience with PostgreSQL
  • Integration experience with DynamoDB
  • Integration experience with MongoDB
  • Integration experience with Snowflake
  • Integration experience with Cloudera
  • Integration experience with Domino Server
  • Performance tuning and optimization in Spark/Databricks
  • Experience with version control and DevOps practices
  • Databricks Certification(s)
  • Experience with Delta Lake and Unity Catalog
  • Familiarity with streaming frameworks and real-time data processing
  • Knowledge of data governance and security best practices
  • Experience in Agile/Scrum delivery models
  • Experience with Terraform or Infrastructure as Code
  • Exposure to ML/data science platforms
  • Experience with orchestration tools such as Airflow or Azure Data Factory
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The Company
HQ: New York, NY
30,246 Employees
Year Founded: 1999

What We Do

Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.

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