Data Engineer
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Role details
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Job description
The Data Engineer as part of the Data Management and BI will participate in the development and deployment of Data Warehouse and BI products aligned to the business’s strategic plans and the HBS Shared Services initiative. These resources will be embedded in product delivery pods supporting recruiting, onboarding, credentialing, contract automation, Flex Path, compensation, QGenda automation, and KPI reporting. The employee will build the governed data foundation required for AI-enabled workflows, automation, dashboards, decision support, and agent-assisted product delivery. Responsibilities
- Data Engineer as part of the Data Management and BI should be able to effectively communicate complex ideas to a diverse population, demonstrate a forward-looking perspective, and support tactical decision-making processes.
- This role will work closely with Product Owners, App Developers, BI teams, Security, Responsible AI, Enterprise Architecture, business stakeholders, and other development teams.
- The candidate should perform all duties with a focus on quality of work and attention to detail with a high level of self-management and self-awareness, while helping convert manual processes, spreadsheets, and disconnected workflows into governed, scalable data solutions.
Requirements
- Specific expertise/experience in data acquisition, data cleansing, parsing, validation, reconciliation, lineage, and documentation required.
- Specific expertise/experience in data analysis, modeling and visualization required.
- 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 required.
- 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 required.
- Experience integrating multiple source systems and preparing data for AI agents, applications, automation workflows, dashboards, and reporting required.
- 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
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