Data Engineer at Neighborhood Family Practice in May Dugan - Cleveland, OH 44113

Job description

• Salary Range
• $75,000.00 - $85,000.00 Salary
• Position Type
• Full Time
• Position Overview: Describes the overall purpose of the position or why the position exists
• The Data Engineer designs, develops, and maintains secure, scalable data infrastructure that integrates clinical, operational, financial, quality, and value-based care data. This role builds reliable data pipelines, establishes data-quality controls, and creates trusted datasets for reporting, analytics, regulatory requirements, and organizational decision-making. The Data Engineer collaborates with clinical, operational, technical, and analytics teams to improve data accessibility, interoperability, governance, and meaningful use across NFP.

Responsibilities

• Essential Duties and Responsibilities: The following description is a general representation of the essential duties and responsibilities of the position.
• Design, develop, test, deploy, and maintain automated data pipelines across Epic’s financial, operational, quality, and partner data sources such as NetSuite, PayCom and Pioneer.
• Build and maintain scalable data models, data warehouses, and curated datasets supporting Power BI reporting and advanced analytics.
• Develop automated processes for data extraction, transformation, validation, reconciliation, and monitoring.
• Establish data-quality controls that identify missing, duplicate, inconsistent, or inaccurate information.
• Troubleshoot dataflow, interface, integration, and reporting issues in partnership with clinical, operational, and technical teams.
• Collaborate with data analysts and business leaders to translate reporting requirements into sustainable technical solutions.
• Maintain clear technical documentation, including data dictionaries, source-to-target mappings, business rules, pipeline dependencies, and system workflows.
• Apply HIPAA, privacy, information-security, and role-based access requirements throughout the data lifecycle.
• Monitor pipeline performance, investigate failures, and implement sustainable solutions that reduce manual intervention.
• Educate staff on data definitions, collection standards, system workflows, and the downstream effects of documentation practices.
• Participate in data governance, change management, testing, and validation for new systems and reporting initiatives.
• Other duties as assigned.

Requirements

• The requirements listed below are representative of the knowledge, skills, abilities, experience, and education an individual must possess to be able to perform the essential duties and responsibilities successfully. Reasonable accommodation may be made to enable individuals with disabilities to perform these essential duties and responsibilities.
• Bachelor’s degree in computer science, Information Technology, or similar field strongly preferred. Equivalent experience in lieu of formal education accepted.
• 3+ years experience in data engineering or similar role strongly preferred.
• Knowledge and Skills:
• Advanced SQL skills, including query optimization and relational data modeling
• Experience building automated ETL or ELT pipelines
• Experience using Python for data processing, validation, scripting, and automation
• Experience supporting data warehouses, reporting databases, or analytics platforms
• Understanding of data-quality controls, testing, reconciliation, and technical documentation
• Knowledge of healthcare, privacy and security requirements
• Experience with Microsoft Azure and Azure Data Factory
• Experience developing semantic models or datasets for Microsoft Power BI
• Experience with Epic, OCHIN, or comparable electronic health record data
• Familiarity with healthcare interoperability standards and clinical terminology
• Experience with payer, claims, quality-measure, UDS, population health, or value-based care data
• Experience working in an FQHC, community health center, or ambulatory healthcare environment

Skills

Required

• Willing to travel locally between sites.
• SQL
• Python
• ETL/ELT
• Data warehousing
• Power BI
• Azure
• Azure Data Factory
• Epic
• OCHIN
• HIPAA