Senior Lead Analyst, Enterprise Data Governance​ (Remote)

Stryker•Mahwah, NJ
•$118,000 - $255,700•Remote

About The Position

As a Senior Lead Analyst, Enterprise Data Governance, you will own the execution and ongoing management of the enterprise data quality framework, methodology, and measurement approach across data domains. You will provide an independent view of data quality performance to help leaders understand business risks arising from data issues and the measurable value of improvements. You will lead the Critical Data Element (CDE) approach, establish quality measures and thresholds, develop executive and Board-level scorecards, and drive data quality remediation to its source. The role is remote. Candidates in Eastern or Central time zones are preferred to accommodate business needs. Travel is 10%.

Requirements

  • Bachelor’s degree in information systems, Data Management, Business, or a related field.
  • At least 6 years in data quality, data management, or analytics, including ownership of an enterprise or multi-domain Data Quality program.
  • Demonstrated experience building Data Quality frameworks, rules, scorecards, and remediation processes.
  • Strong analytical and SQL capability, with comfort profiling and interpreting large data sets.
  • Experience presenting quality performance to senior leadership.

Nice To Haves

  • Master’s degree.
  • Experience with Informatica Data Quality (DQ) or comparable DQ tooling.
  • Experience in a regulated industry with DQ experience, including ALCOA+ and Part 11.
  • Experience quantifying the cost of poor data quality.

Responsibilities

  • Author and maintain the enterprise Data Quality Policy, framework, and methodology; socialize them and drive adoption.
  • Define the CDE methodology and support Domain Working Groups in identifying CDEs and setting defensible thresholds.
  • Build and run Board-level Data Quality scorecards; establish baselines and report trends against them.
  • Oversee remediation by tracking issues to closure at source, escalating systemic defects, and driving root-cause analysis with process and system owners.
  • Independently assess master data quality reported by Enterprise MDM so measurement is separated from execution.
  • Translate quality performance into business outcomes and cost-of-poor-quality terms, including preventable disputes, working capital, close effort, straight-through processing, and acquisition integration time.
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