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 reported $1654.4M FY26 revenue with 17.4% Y-o-Y growth. We have delivered 24sequential quarters of growth with $436.0M in Q4 FY26 revenue up 3.2% Q-o-Q and 16.2% Y-o-Y growth. Our 27500global team members located in 18 countries have been instrumental in helping the market leaders transform their industries. We have been recognized as theFastest Growing IT Services Brand Globally in the 2026 Brand Finance IT Services 25 Report. We named a Leader in theEverest Group Private Equity (PE) Services PEAK MatrixAssessment 2026andSoftware Product Engineering PEAK MatrixAssessment 2026.

About Position:

We are looking for an experienced Azure Data Engineer with strong expertise in Azure Databricks Snowflake PySpark and SQL. The ideal candidate will be responsible for designing developing and optimizing scalable cloud-based data platforms that enable enterprise analytics business intelligence and data-driven decision-making. You will work on modern data engineering initiatives involving large-scale data processing ETL/ELT development data warehousing and Lakehouse architectures across Azure and Snowflake ecosystems. The role requires strong technical expertise problem-solving skills and the ability to collaborate effectively with business and technology teams.

- Role: Azure Data Engineer - (Snowflake & ADB)
- Location: Pune Bengaluru Chennai
- Experience: 3 to 8 years




- Job Type: Full Time Employment

What Youll Do:

- Design develop and maintain scalable data pipelines using Azure Databricks and PySpark.
- Build and optimize ETL/ELT workflows to process large volumes of structured and unstructured data.
- Develop and manage Snowflake data warehouse solutions including data loading transformation and performance optimization.
- Create reusable frameworks for data ingestion orchestration data validation and transformation.
- Integrate data from multiple enterprise systems databases APIs and cloud platforms into Azure Data Lake and Snowflake environments.
- Design and implement modern Lakehouse architectures using Azure Databricks and Delta Lake.
- Optimize data processing workloads for performance scalability reliability and cost efficiency.
- Implement data quality checks governance standards security controls and monitoring frameworks.
- Collaborate with business stakeholders architects analysts and engineering teams to deliver scalable data solutions.
- Troubleshoot and resolve production issues related to data pipelines cloud platforms and analytics environments.
- Participate in code reviews CI/CD implementation release management and deployment automation activities.
- Support continuous improvement initiatives and contribute to data platform modernization programs.

Expertise Youll Bring:

- 3-8 years of experience in Data Engineering and Cloud Data Platform development.
- Strong hands-on expertise in Azure Databricks PySpark Spark SQL and Delta Lake.
- Proven experience with Snowflake including data loading transformations data sharing and performance tuning.
- Strong SQL expertise including complex query development optimization troubleshooting and data analysis.




- Experience with Azure services such as Azure Data Factory (ADF) Azure Data Lake Storage (ADLS Gen2) Azure Key Vault and Azure DevOps.
- Good understanding of Data Warehousing concepts Dimensional Modeling ETL/ELT Architecture and Lakehouse Architecture.
- Experience developing and supporting enterprise-scale data pipelines and cloud analytics solutions.
- Knowledge of data governance data quality management metadata and security best practices.
- Experience with Git CI/CD pipelines source control and Agile software development methodologies.
- Solid analytical problem-solving debugging and troubleshooting capabilities.
- Ability to work independently and collaboratively within cross-functional teams.
- Excellent communication and stakeholder management skills.

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.

Required Experience:

IC

📌 Azure Data Engineer (Snowflake & ADB) (Pune)
🏢 Persistent Systems
📍 Pune