Databricks Developer / Data Architect

ExlService Holdings, Inc.; India; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

ExlService Holdings, Inc. seeks an experienced Databricks Developer / Data Architect to design, implement, and optimize modern data platforms and ETL pipelines using Databricks and cloud-native technologies.

The role focuses on data architecture, Lakehouse implementation, Medallion Architecture, and scalable ETL across Azure and AWS. The candidate will establish Databricks workspaces, configure data integrations and Federation, and build enterprise-grade ETL workflows to enable high-performance

Qualifications

• 5+ years of experience in Data Engineering / Data Architecture.
• Strong hands-on experience with Databricks platform.
• Expertise in Python, Spark, PySpark and SQL.
• Strong understanding of Lakehouse Architecture, Medallion Architecture, Data Modeling and ETL/ELT design patterns.
• Cloud experience with Microsoft Azure and AWS.
• Experience integrating with PostgreSQL, DynamoDB, MongoDB, Snowflake, Cloudera, Domino Server.

Responsibilities

• 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) for data processing and analytics.
• Set up Lakehouse Federation and data connectors for multi-source integration.
• Develop logical and physical data models for structured and semi-structured data.
• Ensure data quality, security, scalability, and performance optimization.
• 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.
• 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 Data Scientists, Analysts, and Business stakeholders.

Skills

Python

Spark

PySpark

SQL

Lakehouse

Medallion Architecture

Data Modeling

ETL/ELT

Azure

AWS

PostgreSQL

DynamoDB

MongoDB

Snowflake

Cloudera

Domino Server

DevOps

Tools

Databricks

Delta Lake

Unity Catalog

Terraform

Job description

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