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 what's 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 disruptor's mindset, commitment to client success, and agility to thrive in the energetic environment have enabled us to sustain our growth momentum. Persistent has been recognized across top industry platforms for innovation, leadership, and inclusion. We reported $1,654.4M FY26 revenue with 17.4% Y-o-Y growth.

We have delivered 24 sequential quarters of growth with $436.0M in Q4 FY26 revenue, up 3.2% Q-o-Q and 16.2% Y-o-Y growth. Our 27,500+ global team members, located in 18 countries, have been instrumental in helping the market leaders transform their industries.

About Position:

We are looking for an experienced Senior Databricks Data Engineer to build, optimize, and maintain scalable data platforms and pipelines on the Databricks ecosystem. The ideal candidate will have extensive hands-on expertise in Databricks, Apache Spark, Delta Lake, cluster management, performance tuning, and large-scale data processing. You will play a critical role in designing cloud-native data solutions, enabling advanced analytics, and delivering high-performance data platforms that support enterprise business needs.

- Role: Senior Databricks Data Engineer
- Location: All Persistent Locations
- Experience: Between 7 to 12 Years
- Job Type: Full Time Employment

What You'll Do:

- Develop, maintain, and optimize ETL/ELT pipelines using Databricks, PySpark, SQL, and Databricks Notebooks.
- Design and implement data processing workflows across Bronze, Silver, and Gold layers using Delta Lake architecture.
- Build scalable batch and real-time streaming data pipelines using Spark Structured Streaming.




- Perform Spark application tuning, cluster optimization, workload balancing, and cost optimization activities.
- Develop reusable frameworks and components to improve data engineering productivity and scalability.
- Collaborate with data architects, analysts, business stakeholders, and engineering teams to deliver data-driven solutions.
- Ensure data quality, data validation, lineage tracking, and adherence to data governance standards.
- Integrate Databricks solutions with cloud-native services across AWS, Azure, or Google Cloud environments.
- Implement security, monitoring, logging, and operational best practices across data platforms.
- Automate deployment processes and leverage CI/CD pipelines for efficient code promotion and release management.
- Troubleshoot and resolve data pipeline, cluster, performance, and production issues.
- Support large-scale data migration, modernization, and lakehouse implementation initiatives.
- Participate in architecture reviews and recommend improvements for scalability, reliability, and performance.

Expertise You'll Bring:

- 7–12 years of experience in Data Engineering, Analytics, and Enterprise Data Platforms.
- Hands-on experience delivering multiple end-to-end Databricks implementation projects.
- Strong expertise in Databricks platform development, administration, and optimization.
- Deep knowledge of Apache Spark architecture, Spark internals, and distributed computing concepts.
- Extensive experience with PySpark, Spark SQL, Structured Streaming, and Delta Lake.
- Strong experience in designing and implementing scalable ETL/ELT frameworks.
- Expertise in Databricks cluster sizing, configuration, workload management, and performance tuning.




- Experience diagnosing and resolving performance bottlenecks in large-scale data environments.
- Strong SQL skills with expertise in query optimization and data transformation techniques.
- Experience working with cloud platforms such as Azure, AWS, or Google Cloud, with deep expertise in at least one.
- Knowledge of data lake, lakehouse, and modern data architecture patterns.
- Experience implementing CI/CD processes and production deployment strategies for data platforms.
- Strong understanding of data governance, security, compliance, and operational best practices.
- Experience working with Git, version control systems, and Agile delivery methodologies.
- Excellent analytical, troubleshooting, and problem-solving skills.
- Strong communication and stakeholder management capabilities.

Benefits:

- Competitive salary and benefits package
- Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications
- Prospect 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.

Let's unleash your full potential at Persistent - persistent.com/careers

“Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.”

📌 Senior Databricks Data Engineer (Pune)
🏢 Persistent
📍 Pune