Senior Azure Data Engineer

Role overview

Responsibilities

• Collaborate with product owners, business analysts, architects, and software engineers to deliver solutions aligned with agile roadmaps.
• Design, develop, test, and maintain large-scale data applications and pipelines using Azure, Databricks, Spark, and cloud-native technologies.
• Build integrations across relational and non-relational databases; design APIs and data services for enterprise applications.
• Evaluate functional and non-functional requirements and deliver high-quality solutions.
• Improve CI/CD, DevOps, and automation practices; build and maintain deployment pipelines.
• Implement monitoring, logging, observability, reliability, fault tolerance, deployment planning, and automated testing.
• Work with Data-as-a-Service and Container-as-a-Service architectures; manage incidents through ServiceNow or ticketing systems.
• Support production environments and troubleshoot data engineering issues; help ensure platform scalability, security, resilience, and accuracy.

Experience and qualifications

• 6–10 years of data engineering and cloud platform development experience.
• At least 6 years with Azure and/or AWS services; at least 5 years hands-on with Azure Databricks and Apache Kafka.
• Strong Spark-based data processing experience and at least 2 years with Snowflake Data Cloud.
• Experience designing scalable ETL/ELT pipelines and working with RESTful APIs and integration frameworks.
• Experience with relational databases such as SQL Server, Oracle, or PostgreSQL, and with non-relational databases and modern storage.
• Knowledge of distributed data processing, big data, Agile, DevOps, CI/CD, version control, and infrastructure automation.
• Experience with monitoring, logging, and observability; exposure to ServiceNow or similar platforms.
• Strong analytical, problem-solving, and communication skills.
• Bachelor's degree in Engineering, Computer Science, Information Technology, or equivalent experience.

Technology skills

• Azure, Azure Databricks, Apache Kafka, Spark, and Snowflake are central technologies.
• Role includes relational and non-relational databases, RESTful APIs, ETL/ELT, distributed processing, and big data.
• Appended listing details identify Databricks, Azure, PySpark, and SQL as required skills; they list Databricks, Azure, PySpark, and SQL as desirable skills as well.

Workplace

• The posting states that Persistent supports hybrid work and flexible hours.

Benefits

• Benefits include salary and benefits package, health check-ups, and insurance coverage for life, personal accident, and hospitalization.
• The company describes talent development, higher education and certification support, flexible work hours, and employee engagement initiatives.