Database Architect

Acro Service Corp; Saint Paul (MN); On-site; USD 120,000 - 160,000; Full time

Job summary

Acro Service Corp seeks a Data Platform Lead to oversee data ingestion, transfer, cataloging, governance, quality, and accessibility, partnering with R&D, Clinical teams, IT/Cloud, and external partners.

The role focuses on trustworthy, compliant datasets for AI/ML development, validation, and regulatory submissions, requiring strong leadership and data management expertise in regulated environments.

Qualifications

• Bachelor's degree in a relevant field as listed.
• 5+ years in data management, data operations, or related roles.
• Experience handling large, diverse datasets (clinical/imaging/time-series).
• Experience in data governance, metadata, cataloging, and quality.
• Experience coordinating data transfers and lifecycle activities.
• Knowledge of Azure or comparable cloud data platforms.
• Strong privacy, security, and regulatory understanding.
• Excellent communication and cross-functional leadership.

Responsibilities

• Oversee data ingestion, transfer, cataloging, governance, and quality.
• Partner with R&D, Clinical, IT/Cloud, field personnel, and vendors.
• Ensure datasets are trustworthy, compliant, and AI/ML-ready.
• Support regulatory submissions and validation activities.

Skills

Data governance

SQL

Python

Stakeholder leadership

Data quality

Cloud platforms

Project management

Regulated industry

Education

Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, Health Informatics, Biomedical Engineering, or related

Tools

Databricks

Microsoft Purview

HL7/FHIR

Job description

W2 employment only. C2C and 1099 arrangements are not available.

This role combines data platform leadership with operational execution. The successful candidate will oversee data ingestion, transfer, cataloging, governance, standardization, quality, and accessibility while partnering closely with R&D engineers, Clinical teams, IT/Cloud organizations, field personnel, physicians, external partners, and vendors. The role will ensure that clinical and field-derived datasets are readily available, trustworthy, compliant, and optimized for AI/ML development, validation, and regulatory submission activities.

Required Qualifications

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, Health Informatics, Biomedical Engineering, or a related discipline.
• 5+ years of experience in data management, data operations, data engineering, clinical data support, or related roles.
• Demonstrated experience managing large and diverse datasets, including clinical, imaging, mapping, or time-series data.
• Experience implementing data governance, metadata management, cataloging, and data quality processes.
• Experience coordinating data transfers, data lifecycle activities, or multi-stakeholder data initiatives.
• Knowledge of cloud-based data platforms such as Azure, Databricks, or comparable environments.
• Strong understanding of data privacy, security, compliance, and regulated industry requirements.
• Excellent communication, stakeholder management, and cross-functional leadership skills.
• Strong organizational, project management, and execution capabilities.
• Working knowledge of SQL and experience with scripting or programming languages such as Python.

Preferred Qualifications

• Experience within medical devices, healthcare, life sciences, or other regulated R&D environments.
• Familiarity with electrophysiology, cardiac mapping, and clinical imaging data.
• Knowledge of clinical and imaging standards including DICOM, HL7, and FHIR.
• Experience supporting AI/ML development through dataset preparation, annotation, validation, MLOps, or model governance activities.
• Experience with data governance tools such as Microsoft Purview, Collibra, or Alation.
• Knowledge of FDA regulations, 21 CFR Part 11, GxP requirements, HIPAA, and GDPR.
• Experience building or modernizing enterprise data management platforms and processes.
• Experience managing external data providers, labeling vendors, and strategic data partnerships.