Azure Data Engineer - (Snowflake & ADB)

Role overview

Responsibilities

• Design, develop, and maintain Azure Databricks and PySpark pipelines; build ETL/ELT workflows for structured and unstructured data.
• Develop Snowflake warehouse solutions, including data loading, transformations, and performance optimization.
• Create reusable ingestion, orchestration, validation, and transformation frameworks; integrate enterprise systems, databases, APIs, and cloud platforms.
• Implement Lakehouse architecture with Databricks and Delta Lake; optimize performance, scalability, reliability, and cost.
• Implement data quality, governance, security, and monitoring; troubleshoot production issues.
• Collaborate across business and technical teams and contribute to code reviews, CI/CD, release management, deployment automation, and modernization.

Experience and technical requirements

• 3–8 years in data engineering and cloud data platform development.
• Hands-on Azure Databricks, PySpark, Spark SQL, and Delta Lake experience; proven Snowflake experience.
• Strong SQL skills and experience with Azure Data Factory, Azure Data Lake Storage Gen2, Azure Key Vault, and Azure DevOps.
• Understanding of data warehousing, dimensional modeling, ETL/ELT, and Lakehouse architecture.
• Experience with enterprise pipelines, cloud analytics, governance, data quality, metadata, security, Git, CI/CD, and Agile.
• Strong analytical, debugging, problem-solving, collaboration, communication, and stakeholder-management skills.

Benefits

• Competitive salary and benefits package; talent development, quarterly growth opportunities, and company-sponsored education and certifications.
• Flexible work hours, employee engagement initiatives, annual health check-ups, and insurance coverage.

Workplace

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