Manager, Data Acquisitions

Position Summary:

Our client is seeking a manager to lead the Data Acquisitions engineering team that is responsible for the reliable, scalable intake and preservation of enterprise data across clinical, operational, research, and partner sources. This manager will oversee software engineering delivery for high-volume, business-critical data pipelines using Azure Databricks and related Azure services, configuration-driven development, automated testing, CI/CD, and Agile practices. You will ensure that capabilities align with enterprise architecture, governance, security, and operational requirements and provide the authoritative data-source foundation for the enterprise data platform and clinical research initiatives. Additionally, you will be responsible for building a highly technical team, establishing measurable service and delivery outcomes, and ensuring human and financial resources are effectively deployed. 

This position is full-time, hybrid/onsite, and requires living and working in Central Indiana. 

 Responsibilities:

• Oversees the productivity of assigned teams and resources. 
• Ensures that project outcomes conform to business and clinical needs. 
• Demonstrates consistency & reliability in execution. 
• Builds a functional team and ensures that human and financial resources are effectively deployed. 
• Establishes metrics and tracks improvements. 
• Manages team members and drives the ownership mindset necessary to achieve departmental plans and direction. 
• Reviews and evaluates work of staff and prepares performance reports.
• Provides technical leadership for a software development team designing, building, testing, deploying, and supporting enterprise-scale data acquisition pipelines and reusable ingestion capabilities.
• Leads acquisition and continuity planning for complex clinical, operational, research, partner, and multimodal data sources, including the transition from one EHR to another and support for reusable enterprise and novel data product projects.
• Owns SLA-driven delivery and production operations for business-critical data acquisition at TB/PB scale and more than 5,000–10,000 daily executions, including observability, incident response, recovery, performance, capacity, and cost management.
• Applies enterprise architecture and software engineering practices across Azure Databricks and related Azure services, including configuration-driven and metadata-driven development, infrastructure as code, source control, automated testing, CI/CD, environment promotion, security, governance, and platform migration.
• Maintains working knowledge of enterprise and healthcare data integration patterns and exchange standards, including batch, streaming, files, APIs, HL7, FHIR, and CCDA, and ensures source provenance, reconciliation, lineage, and continuity are built into delivery.

Qualifications:

• Bachelor's degree preferred or equivalent experience.
• Requires 5-7 years of relevant experience in an IS/IT and/or management role.
• Requires a strong technical background in data engineering and software delivery, with demonstrated understanding of Azure Databricks, SQL and Python-based development, cloud data platforms, configuration-driven solutions, source control, automated testing, CI/CD, and Agile delivery workflows.
• Requires a demonstrated fundamental understanding of project accounting and financial management.
• Requires an understanding of general Information Management roles, responsibilities, and best practices.
• Preferred: Relevant coursework or certifications in Azure Databricks, Azure data engineering or architecture, Agile delivery, DevOps/CI/CD, ITIL, project management, or continuous improvement. Demonstrated hands-on leadership of comparable technical teams may be considered in place of certifications.
• Preferred: Experience managing contractors and vendors.
• Preferred: Experience acquiring, managing, and securely delivering large-scale multimodal data, including genomics, medical imaging, unstructured text, and wearable or device-generated data, to support distributed, edge, and clinical research use cases.