Data Engineer IV

Epitec is seeking experienced Data Engineer IV professionals to join a large-scale enterprise data engineering initiative. This role involves designing and delivering modern data solutions within the Azure ecosystem to drive reporting, analytics, and business intelligence across the organization.

Responsibilities:

• Design, develop, and maintain scalable data pipelines using Databricks and Azure Data Factory
• Build Spark-based data transformation and processing solutions for large-scale enterprise environments
• Move, integrate, and transform data from multiple source systems into Azure Data Lake environments
• Utilize Unity Catalog and Delta Tables to manage and optimize enterprise data assets
• Develop and support Power BI datasets, semantic models, reports, dashboards, and visualizations
• Partner with business stakeholders to gather and translate reporting and analytics requirements
• Perform unit, integration, and system testing to ensure data accuracy and quality
• Validate end-to-end processing of required files, data, and transactions
• Troubleshoot and resolve data pipeline, reporting, and performance issues
• Participate in Agile ceremonies, sprint planning, backlog grooming, and delivery activities
• Lead technical discussions, mentor team members, and promote engineering best practices

Requirements:

• 5+ years of experience with Databricks
• Databricks Certification required
• 5+ years of experience with Azure Data Factory
• 5+ years of hands-on SQL development
• 3+ years of Power BI development experience
• Strong experience with Spark programming
• Experience working with Azure Data Lake
• Experience with Unity Catalog and Delta Tables
• Strong understanding of data integration, transformation, and validation processes
• Experience performing unit testing and system testing of data solutions
• Strong verbal and written communication skills
• Experience working in Agile environments
• Proven technical leadership and mentoring experience
• Experience in large enterprise data environments
• Azure cloud certifications
• Experience with CI/CD and DevOps practices for data engineering
• Knowledge of data governance, data quality, and security best practices