Senior Data Engineer

Press Ganey is the leading experience measurement, data analytics, and insights provider for complex industries. They are seeking a Senior Data Engineer to design, develop, and support solutions for transporting, storing, and analyzing analytical data, while evolving their enterprise data strategy and capabilities.

Responsibilities:

• Create data architecture, pipelines, and analytical solutions to meet software and data science requirements for various PG-MX Healthcare Products
• Identify, evaluate, select, and prove out new technologies and toolsets
• Create and execute Proofs of Concept and Proofs of Technology
• Lead and direct the work of others in data dependent projects
• Collaborate with software development, business teams, analysts, and data scientists to establish data storage, pipeline, and structure requirements
• Design, develop, and maintain ETL/ELT pipelines using Databricks (PySpark, Delta Lake, SQL)
• Implement Data Lakehouse architecture leveraging Databrick Unity Catalog, Delta Live Tables, and Workflows
• Build and optimize data ingestion frameworks for structured and unstructured data from diverse sources
• Identify and plan for data storage performance requirements
• Optimize Databricks clusters, jobs, and queries for performance and cost efficiency
• Collaborate with software development, business teams, and data scientists to create and execute implementations
• Identify impact of implementation on other applications and databases
• Lead and mentor data engineers on data projects
• Implement CI/CD for data pipelines using Git, Databricks Repos, and DevOps tools
• Ensure Data quality, reliability, security compliances across environments
• Build and evolve Trusted Record systems to manage entities across the enterprise
• Design, implement, and evolve solutions around person identity management
• Develop and enforce data governance, lineage, and cataloging standards
• Identify areas of development and need
• Provide targeted training and exploration for team members
• Train and mentor data engineers on standards and best practices

Requirements:

• Minimum of 5 years Data Engineering experience in an enterprise environment
• Bachelor's degree in technology or like field required
• Hands on experience of Azure data technologies (Databricks, Data Factory, Stream Analytics, Data Lake Storage, Synapse), on-premises Microsoft tools (SQL DB and SSIS), and familiar with AWS data technologies
• Proficiency in Python, SQL and distributed data processing frameworks (Spark), and familiar with C#, PowerShell, and APIs
• Significant experience with analytical solutions in relational databases such as MS SQL Server, Oracle, and DB2 as well as experience with NoSQL databases and solutions such as data lakes, document-oriented databases, and graph databases
• Strong understanding of data modeling, schema design, and ETL best practices
• Experience with data lineage, cataloging, and metadata management in Databricks and Unity Catalog
• Skill in data modeling and experience with tools like ER/Studio or Erwin
• Familiarity with version control (Git) and DevOps/CI-CD practices
• Familiarity with SQL performance tuning and Spark optimization techniques
• Excellent problem-solving and communication skills