Data Engineer

Responsibilities

• Effectively communicate complex ideas to a diverse population
• Demonstrate a forward-looking perspective
• Support tactical decision-making processes
• Work closely with Product Owners, App Developers, BI teams, Security, Responsible AI, Enterprise Architecture, business stakeholders, and other development teams
• Build the governed data foundation required for AI-enabled workflows, automation, dashboards, decision support, and agent-assisted product delivery

Requirements

• Specific expertise/experience in data acquisition, data cleansing, parsing, validation, reconciliation, lineage, and documentation
• Specific expertise/experience in data analysis, modeling and visualization
• Specific expertise/experience in data technologies such as Google BigQuery, Teradata Vantage, Oracle, SQL Server, or other DBMS
• Specific expertise/experience in the areas of data structures and data warehousing
• Understanding of MicroStrategy, Business Objects, Power BI, or other Enterprise BI tools
• Strong experience implementing and overseeing data quality, governance, testing, validation, reconciliation, lineage, documentation, and change management processes
• Specific expertise/experience with ETL/ELT and development tools such as Teradata Protocol Transport, SSIS, Python, PowerShell, and cloud data services
• Specific expertise/experience building scalable pipelines, data models, curated datasets, and governed data products
• Experience integrating multiple source systems and preparing data for AI agents, applications, automation workflows, dashboards, and reporting
• Experience with GCP, Python, MS SQL Server, Teradata, and BI platforms preferred
• Knowledge of Clinical and Financial Applications
• Knowledge of EMR or Practice Management Systems such as E-Clinical Works, Epic, GE Centricity, NextGen, etc.
• Articulates existing system structure, constraints and deficiencies with product to development, customer engagement, architecture and support teams
• Contributes to technology option discussions and decisions for a product
• Pursues new methods and solutions, thinks outside the box, connects disparate ideas, is comfortable using unorthodox methods
• Experience with a variety of Database Management Systems (DBMS) especially Teradata, SQL Server, Oracle, Netezza, etc.
• Healthcare/provider lifecycle experience preferred, including recruiting, onboarding, credentialing, contract automation, QGenda scheduling, compensation, Flex Path, and KPI reporting
• Experience with AI, automation, agentic workflows, or decision-support products preferred
• Experience supporting agentic delivery models across business-outcome product pods