Azure Data Engineer – Snowflake & Databricks
Persistent Systems
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Benefits offered by this job
Job summary
Persistent is seeking an experienced Azure Data Engineer to design, build, and optimize scalable data platforms using Azure Databricks, Snowflake, PySpark and SQL. You will develop robust data pipelines, implement modern data warehousing, and enable enterprise analytics across cloud-native architectures.
This full-time role is based in India with multiple city options (Pune, Bengaluru, Chennai). You will collaborate with architects, analysts and business stakeholders in an Agile environment to
Qualifications
- 4–10 years of Data Engineering and Analytics experience.
- Hands-on experience with Azure Databricks, PySpark, Spark SQL, and Delta Lake.
- Expertise in Snowflake data ingestion, transformation, and optimization.
- Strong SQL development and performance tuning.
- Experience with Azure services (ADF, ADLS, Key Vault, DevOps).
- Knowledge of data warehousing concepts and dimensional modeling.
- Experience designing ETL/ELT architectures and data lakehouse concepts.
- Experience with large-scale enterprise datasets.
Responsibilities
- Design, develop, and maintain scalable data pipelines using Azure Databricks and PySpark.
- Build and optimize ETL/ELT workflows for structured, semi-structured, and unstructured data.
- Develop Snowflake data warehouses with data modeling and performance tuning.
- Create reusable data ingestion, transformation, validation, and orchestration frameworks.
- Integrate data from multiple systems into Azure Data Lake and Snowflake.
- Develop batch and real-time data processing solutions.
- Implement data quality, governance, monitoring, and security practices.
- Design and support modern data lakehouse architectures.
- Collaborate with stakeholders to deliver data-driven solutions.
- Participate in code reviews and enforce engineering best practices.
- Implement CI/CD pipelines and deployment automation for data engineering.
- Create documentation, data flow diagrams, and operation procedures.
Skills
Tools
Job description
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.
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.
We are looking for an experienced Azure Data Engineer with strong expertise in Azure Databricks, Snowflake, PySpark, and SQL to design, develop, and optimize scalable data platforms and cloud-based data solutions. The ideal candidate will be responsible for building robust data pipelines, implementing modern data warehousing solutions, and enabling enterprise analytics and business intelligence initiatives. This role requires hands‑on experience working with large-scale datasets, cloud-native architectures, ETL/ELT processes, and modern data engineering technologies across Azure and Snowflake ecosystems. You will collaborate with architects, analysts, and business stakeholders to deliver high-performance and reliable data solutions.
- Role: Azure Data Engineer – Snowflake & Databricks
- Location: Pune, Bengaluru, Chennai
- Experience: 4 to 10 Years
- Job Type: Full-Time Employment
- Design, develop, and maintain scalable data pipelines using Azure Databricks and PySpark.
- Build and optimize ETL/ELT workflows for processing structured, semi-structured, and unstructured data.
- Develop and manage Snowflake data warehouse solutions, including data modeling and performance optimization.
- Create reusable frameworks for data ingestion, transformation, validation, and orchestration.
- Integrate data from multiple enterprise systems into Azure Data Lake and Snowflake platforms.
- Develop scalable batch and real-time data processing solutions.
- Optimize data processing workloads for performance, scalability, and cost efficiency.
- Implement data quality, governance, monitoring, and security best practices.
- Design and support modern data lakehouse architectures.
- Collaborate with business stakeholders, architects, and analytics teams to deliver data-driven solutions.
- Perform data analysis and troubleshoot production issues related to data pipelines and cloud platforms.
- Support data migration and modernization initiatives.
- Participate in code reviews and enforce engineering best practices.
- Implement CI/CD pipelines and deployment automation processes for data engineering solutions.
- Create and maintain technical documentation, data flow diagrams, and operational procedures.
- Participate in Agile ceremonies including sprint planning, stand-ups, reviews, and retrospectives.
- 4–10 years of experience in Data Engineering and Analytics projects.
- Strong hands‑on experience with Azure Databricks, PySpark, Spark SQL, and Delta Lake.
- Proven expertise in Snowflake including data ingestion, transformation, optimization, and data sharing.
- Strong SQL development skills with experience in query optimization and performance tuning.
- Experience with Azure services including Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure Key Vault, Azure DevOps.
- Strong understanding of data warehousing concepts and dimensional modeling.
- Experience designing and implementing ETL/ELT architectures.
- Knowledge of Data Lake and Lakehouse architecture principles.
- Experience working with large-scale enterprise datasets.
- Hands‑on experience with Git and source code management practices.
- Experience implementing CI/CD pipelines and deployment automation.
- Familiarity with data governance, data quality, and security frameworks.
- Strong analytical, troubleshooting, and problem‑solving skills.
- Experience working in Agile and Scrum delivery environments.
- Ability to collaborate effectively with business stakeholders and technical teams.
- Excellent communication and stakeholder management skills.
- Ability to work independently and manage multiple priorities in a fast‑paced environment.
- 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
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
“Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.”
Databricks,ETL
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