Databricks Architect

About Persistent

We are an AI-led platform-driven Digital Engineering and Enterprise Modernization partner combining deep technical expertise and industry experience to help our clients anticipate whats next. Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above. We work with many industry-leading organizations across the world including 20 Fortune 50 companies and 4 of the 5 top banks in both the US and India and numerous innovators across the healthcare ecosystem.

Our disruptors mindset commitment to client success and agility to thrive in the dynamic environment have enabled us to sustain our growth momentum. Persistent has been recognized across top industry platforms for innovation leadership and inclusion. We have delivered 22 sequential quarters of growth with $406.2M in Q2 FY26 revenue up 4.2% Q-o-Q and 17.6% Y-o-Y growth. Our 26000 global team members located in 18 countries have been instrumental in helping the market leaders transform their have been named the fastest-growing Indian IT services brand in the Brand Finance Indiareport. We were also cited as a Leader in the ISG Provider Lens 2025 for Digital Engineering Services 2025 and the Everest Group Talent Readiness for Next-generation Application Services PEAK MatrixAssessment 2025

About Position:

We are looking for an experienced Databricks Architect who can build optimize and maintain scalable data pipelines on the Databricks platform.

• Role: Databricks Architect
• Location: Pune
• Experience: 12 years
• Job Type: Full Time Employment

What Youll Do:

• Develop and maintain ETL/ELT pipelines using Databricks (PySpark SQL Notebooks).
• Design endtoend Lakehouse architecture including ingestion transformation modeling and consumption.
• Define and implement Medallion Architecture (Bronze/Silver/Gold) using Delta Lake.
• Build high-performance ETL/ELT pipelines using PySpark Spark SQL Delta Lake.
• Architect and optimize batch and streaming data pipelines.
• Perform advanced Spark optimization cluster sizing and cost management.
• Implement CI/CD version control and DevOps best practices within Databricks.

Expertise Youll Bring:

• Advanced expertise in:
• Databricks Lakehouse Platform
• PySpark & Spark SQL
• Delta Lake Structured Streaming
• Unity Catalog & governance frameworks
• Strong experience with a major cloud platform (Azure/AWS/GCP).
• Strong understanding of:
• Distributed computing & Spark internals
• Data warehousing concepts
• Data modeling (dimensional normalized Lakehouse modeling)
• ETL/ELT architecture
• Experience in CI/CD pipelines Git orchestration tools.
• Experience in leading largescale data platform implementations.

Benefits:

• Competitive salary and benefits package
• Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications
• Opportunity to work with cutting-edge technologies
• Employee engagement initiatives such as project parties flexible work hours and Long Service awards
• Annual health check-ups
• Insurance coverage: group term life personal accident and Mediclaim hospitalization for self spouse two children and parents

Values-Driven People-Centric & Inclusive Work Environment:

Persistent is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals including those with disabilities and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds.

• We support hybrid work and flexible hours to fit diverse lifestyles.
• Our office is accessibility-friendly with ergonomic setups and assistive technologies to support employees with physical disabilities.
• If you are a person with disabilities and have specific requirements please inform us during the application process or at any time during your employment

Lets unleash your full potential at Persistent - is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.