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Database Architect

Generis Tek

Job Location:

Saint Paul, MN - USA

Hourly Salary: USD 65 - 65

Posted: 20 September 2026 (14 hours ago)

Application Deadline: 18 December 2026

Vacancies: 1 Vacancy

Job Summary

Please Contact: To discuss this amazing opportunity reach out to our Talent Acquisition Specialist Diresh Krishnanat email address can be reached on # .

We have Contract role Database Architect for client at St. Paul MN. Please let me know if you or any of your friends would be interested in this position.

Position Details:
Database Architect- St. Paul MN
Location : St. Paul MN 55117
Project Duration: 12 Months of contract
Shift Timing : 9:00 AM to 5:00 PM (Mon to Fri)
Pay Rate : $65.00 per hour on W2

Position Summary:
Clients Electrophysiology (EP) R&D organization generates an expanding volume of clinical imaging mapping and outcomes data that serves as the foundation for next-generation AI/ML solutions. To accelerate innovation we are seeking a Data Operations & R&D Data Management Manager to lead the strategy processes and infrastructure that enable secure scalable and compliant use of data across the product development lifecycle. 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.

Key Responsibilities:
Data Strategy Platform and Infrastructure

Define and execute a roadmap for modernizing the EP R&D data ecosystem through scalable searchable and automated data management capabilities.
Design and maintain data architecture metadata standards clinical dictionaries and common data models spanning cardiac mapping imaging and clinical datasets.
Partner with IT Cloud and engineering teams to implement and enhance data infrastructure leveraging Azure Databricks and related enterprise platforms.
Evaluate and implement tools supporting data cataloging governance version control lineage labeling storage and AI/ML workflows.
Ensure data systems effectively support both Windows and Linux-based development environments.

Data Operations and Dataset Readiness

Coordinate end-to-end acquisition transfer ingestion validation and management of clinical and field-derived datasets.
Establish processes to ensure completeness integrity traceability and accessibility of data throughout its lifecycle.
Partner with physicians clinical sites field teams and data owners to support strategic data collection and partnership initiatives.
Manage data transfer activities issue resolution status tracking and stakeholder communications to ensure timely delivery of datasets.
Collaborate with engineering and AI/ML teams to address data quality issues missing metadata ingestion failures and standardization gaps.
Support dataset versioning lineage tracking reproducibility and audit readiness for AI/ML model development and validation.

AI/ML Data Enablement

Work directly with AI/ML and R&D engineering teams to understand data requirements and accelerate model development efforts.
Build and improve processes that enable efficient discovery access preparation and validation of datasets.
Oversee labeling and annotation programs including external vendor management quality controls acceptance criteria and development of gold-standard datasets.
Drive continuous improvement initiatives that reduce time spent locating preparing and validating data.

Governance Compliance and Quality

Establish and maintain data governance practices covering access controls retention stewardship quality and security.
Coordinate reviews with Cybersecurity Privacy Legal OEC Clinical and R&D stakeholders to ensure compliant data handling.
Ensure alignment with corporate policies and applicable regulatory requirements including FDA GxP HIPAA GDPR and AI/ML validation expectations.
Maintain audit-ready documentation data lineage records SOPs work instructions approvals and governance artifacts.
Implement data quality monitoring validation checks and remediation processes to ensure ongoing data integrity.

Cross-Functional Leadership

Serve as the primary point of coordination among R&D Clinical IT/Cloud AI/ML field teams and external partners.
Translate technical clinical and business requirements into actionable data solutions and operational plans.
Communicate strategy priorities progress risks and trade-offs to leadership and stakeholders across the organization.
Manage external vendors statements of work timelines deliverables service levels and quality expectations.

Required Qualifications:

Bachelors 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 Mops or model governance activities.
Experience with data governance tools such as MS 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.

What Youll Impact:

Enable R&D teams to rapidly discover access and trust the data required for innovation.
Establish a scalable data foundation supporting AI/ML-powered products and future clinical applications.
Improve operational efficiency compliance data quality and regulatory readiness across the EP organization.
Accelerate the development of next-generation cardiac mapping imaging and AI-enabled technologies that improve patient care.