Senior Azure Data Engineer

About Position:

As a Senior Azure Data Engineer, you will have the opportunity to be part of a high-performing data engineering team focused on transforming healthcare data into actionable insights that improve outcomes and business decisions. We are looking for a highly skilled professional with expertise in Databricks, PySpark, SQL, and Production Support to design, develop, and maintain enterprise-scale data platforms and pipelines.

Role:
Sr. Azure Data engineer

Location:

Pune

Experience:

Between 8 to 10 Years
Job Type: Full Time Employment

What You'll Do:

Design, develop, and maintain scalable data pipelines using Databricks and PySpark.
Build and optimize enterprise-grade ETL and ELT frameworks for large-scale data processing.
Investigate and resolve data quality issues, pipeline failures, and production incidents.
Perform root cause analysis for framework failures, processing issues, and application defects.
Monitor, tune, and optimize Spark workloads for performance, scalability, and reliability.
Develop and optimize SQL queries for data extraction, transformation, validation, and reporting.
Collaborate with business users, architects, and engineering teams to implement robust data solutions.
Support production deployments and provide L2/L3 support for critical data platforms and applications.
Troubleshoot complex data processing, workflow, and platform-related issues.
Implement monitoring, alerting, and operational support processes to improve platform stability.
Ensure data quality, accuracy, consistency, and availability across systems.
Drive adoption of engineering best practices, coding standards, and operational governance.
Participate in code reviews and contribute to continuous improvement initiatives.
Support cloud-native data solutions using Azure and AWS platforms.
Create and maintain technical documentation, operational runbooks, and support procedures.
Contribute to Agile ceremonies including sprint planning, stand-ups, reviews, and retrospectives.

Expertise You'll Bring:

8 to 10 years of experience in Data Engineering, Big Data, and cloud-based data platforms.
Minimum 5+ years of hands-on experience with Databricks and PySpark.
Strong expertise in designing and developing distributed data processing solutions.
Extensive experience in Production Support, incident management, and root cause analysis.
Strong SQL development skills with experience in query optimization and performance tuning.
Experience building and supporting complex ETL/ELT pipelines and large-scale data frameworks.
Strong debugging, troubleshooting, and performance optimization capabilities.
Hands-on experience with Azure or AWS cloud platforms.
Experience working with Spark optimization techniques, job performance tuning, and cluster management.
Knowledge of Delta Lake architecture and modern Lakehouse implementations.
Understanding of data governance, data quality, and data security best practices.
Familiarity with CI/CD pipelines, Dev Ops practices, and deployment automation.

Experience with monitoring, observability, and operational support tools.
Strong analytical and problem-solving skills with the ability to resolve complex technical issues.
Excellent communication and stakeholder management capabilities.
Bachelor's degree in Engineering, Computer Science, Information Technology, or equivalent experience.

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…