Staff Data Engineer

Press Ganey is the leading experience measurement, data analytics, and insights provider for complex industries. They are seeking an experienced Staff Data Engineer to design, develop, and maintain enterprise-scale data infrastructure, leveraging Azure and Databricks technologies, while collaborating with analytics and business teams to enable data-driven decision-making.

Responsibilities:

• Design, build, and optimize data pipelines and workflows in Azure and Databricks, including Data Lake and SQL Database integrations
• Implement scalable ETL/ELT frameworks using Azure Data Factory, Databricks, and Spark
• Optimize data structures and queries for performance, reliability, and cost efficiency
• Drive data quality and governance initiatives, including metadata management and validation frameworks
• Collaborate with cross-functional teams to define and implement data models aligned with business and analytical requirements
• Maintain clear documentation and enforce engineering best practices for reproducibility and maintainability
• Ensure adherence to security, compliance, and data privacy standards
• Mentor junior engineers and contribute to establishing engineering best practices
• Support CI/CD pipeline development for data workflows using GitLab or Azure DevOps
• Partner with data consumers to publish curated datasets into reporting tools such as Power BI
• Stay current with advancements in Azure, Databricks, Delta Lake, and data architecture trends

Requirements:

• Advanced proficiency in Azure 5+ years (Data Lake, ADF, SQL)
• Strong expertise in Databricks (5+ years), Apache Spark (5+ years), and Delta Lake (5+ years)
• Proficient in SQL (10+ years) and Python (5+ years); familiarity with Scala is a plus
• Strong understanding of data modeling, data governance, and metadata management
• Knowledge of source control (Git), CI/CD, and modern DevOps practices
• Familiarity with Power BI visualization tool
• Bachelor's or Master's degree in Computer Science, Data Science, or related field
• 7+ years of experience in data engineering, with significant hands-on work in cloud-based data platforms (Azure)
• Experience building real-time data pipelines and streaming frameworks
• Strong analytical and problem-solving skills
• Proven ability to lead projects and mentor engineers
• Excellent communication and collaboration skills
• Master's degree in Computer Science, Engineering, or a related field
• Exposure to machine learning integration within data engineering pipelines