Senior Data Integrity Analyst - Remote

Stryker•Dallas, TX

1d•$69,500 - $144,200•Remote

About The Position

As a Senior Data Integrity Analyst, you will play a critical role in advancing data accuracy, regulatory compliance, and product traceability across Stryker’s Endoscopy Division. This is an exciting opportunity to lead high‑impact initiatives, influence cross‑functional teams, and strengthen data integrity across complex enterprise systems.

Requirements

Bachelor’s degree.
2+ years of experience in data integrity, data analysis, quality, regulatory, or a related role.
Experience working with enterprise data systems or databases.
Experience designing, maintaining, or using dashboards and data metrics for decision‑making.

Nice To Haves

Experience supporting quality assurance or regulatory data initiatives in a regulated industry.
Experience with process improvement or data quality enhancement projects.

Responsibilities

Investigate field asset data issues using enterprise systems to ensure accuracy, completeness, consistency, and validity across 100% of assigned assets.
Serve as the first point of escalation for field asset issues, resolving or routing requests within defined service‑level expectations.
Lead and coordinate regulatory and quality assurance data initiatives, including requirements definition, testing oversight, documentation updates, and governance activities.
Analyze and report field asset data trends, delinquency status, and risk indicators through dashboards and standardized reporting used by cross‑functional stakeholders.
Educate sales and field teams on compliant field asset program requirements, ensuring consistent execution and accountability.
Research and determine best pathways for resolving missing or non‑compliant assets, including contract, warranty, and inventory disposition decisions.
Communicate timely status updates on delinquent or high‑risk assets to key stakeholders and escalate issues to service, technical, or installation leadership as needed.
Drive continuous improvement by identifying data quality gaps, proposing system or process enhancements, and supporting initiatives that improve efficiency, compliance, and traceability.