Azure Data Engineer

About Position:
We are seeking an experienced Azure Data Engineer to join our growing data and analytics team. In this role, you will be responsible for designing, developing, and supporting scalable data platforms and pipelines using Databricks, Snowflake, PySpark, and SQL. You will work closely with business and technology teams to build reliable data solutions, optimize performance, and ensure operational excellence across enterprise data platforms.
Role: Azure Data Engineer
Location: All Persistent Locations
Experience: 6 to 10 Years
Job Type: Full-Time Employment
What You'll Do:
Design, develop, and maintain scalable data pipelines using Azure Databricks, PySpark, and Snowflake.
Build and optimize ETL/ELT workflows for processing large volumes of structured and unstructured data.
Investigate and resolve data quality issues, pipeline failures, and production incidents.
Perform root cause analysis for framework, infrastructure, and data processing failures.
Monitor, troubleshoot, and optimize Spark workloads for performance, reliability, and scalability.
Collaborate with business stakeholders, architects, analysts, and development teams to gather requirements and deliver data solutions.
Support production deployments and provide L2/L3 production support for critical data platforms.
Implement data validation, monitoring, and governance practices to ensure data quality and integrity.
Establish and enforce engineering best practices for coding standards, testing, performance tuning, and operational excellence.
Develop reusable data engineering frameworks and automation capabilities.
Participate in architecture discussions and contribute to continuous improvement initiatives.
Work with cloud-native technologies and modern data platform architectures.
Expertise You'll Bring:
6-10 years of overall experience in Data Engineering and Big Data technologies.
Strong hands-on experience with Azure Databricks and Snowflake.
Extensive experience in developing complex ETL/ELT data pipelines.
Strong proficiency in PySpark, SQL, and data analysis.
Experience troubleshooting production issues, framework failures, and data inconsistencies.
Proven expertise in distributed data processing and large-scale data engineering solutions.
Strong understanding of data modeling, performance tuning, and optimization techniques.
Experience working with Azure cloud services and modern data platform technologies.
Ability to analyze complex technical issues and implement sustainable solutions.
Strong problem-solving, debugging, and troubleshooting skills.
Familiarity with data governance, data quality, and security best practices.
Excellent communication and collaboration skills with cross-functional stakeholders.
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
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."

Work arrangement
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