Senior Data Engineer

Does analytical data flow through your veins? Are you fluent across cloud, on-premises, platforms, and technologies? Do you have deep healthcare experience? Do you love understanding strategic direction, creating design and direction, then getting fingers on the keyboard? This role is for a Senior Data Engineer with strong data architecture experience. This person will design, develop, and support solutions to transport, store, and analyze our analytical data.

They will be key in evolving and maturing our enterprise data strategy and capabilities.

• 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 Dev Ops tools.

• 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.

• 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#, Power Shell, and APIs.
• Significant experience with analytical solutions in relational databases such as MS SQL Server, Oracle, and DB2 as well as experience with No
  
  SQL 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 Dev Ops/CI-CD practices.
• Familiarity with SQL performance tuning and Spark optimization techniques.
• Excellent problem‑solving and communication skills.

• Minimum of 5 years Data Engineering experience in an enterprise environment.
• Bachelor’s degree in technology or like field required.

Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Press Ganey we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways.

You may be just the right candidate for this or other roles.

Press Ganey Associates LLC is an Equal Employment Opportunity/Affirmative Action employer and well committed to a diverse…