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