Data Governance Lead

Shree Narayani Networking Solutions•Sunnyvale, CA

1d•Onsite

About The Position

Senior Data Governance Lead for a high-tech company’s supply chain organization, with a strong emphasis on consumer hardware and supply chain experience. This 12-month contract, with possible extension, is based onsite in Sunnyvale, California, Monday through Friday. The role acts as a center of excellence for supply chain data governance, working with analytics engineers and cross-functional teams to establish trusted, standardized, and AI-ready data. The lead owns data quality alerting and issue management in Databricks, including detection, triage, routing, service-level expectations, root-cause analysis, and resolution. The role also defines and maintains metric standards and certification requirements for official reporting, and supports a trusted Databricks Gold-layer data foundation with certified models, embedded quality and abnormality checks, metrics views, and data lineage. The position drives dataset readiness assessments for AI use and helps enable natural-language access to certified metrics.

Requirements

Strong background in data governance, data management, or data architecture.
Strong supply chain experience, particularly in consumer hardware.
Experience with Databricks, Unity Catalog, data lineage, and enterprise data platforms.
Expertise in KPI framework design, metric governance, and data modeling.
Experience establishing master data governance programs and enterprise data standards.
Knowledge of AI/ML data readiness, data quality assessment frameworks, and analytics platforms.
Ability to influence cross-functional stakeholders in a matrixed environment without direct authority.
Strong communication, leadership, and mentoring skills.

Nice To Haves

Experience with ThoughtSpot, AtScale, Power BI, Looker, Tableau, or similar analytics platforms.
Familiarity with standardized KPI calculations such as actuals versus targets, rolling averages, period-over-period comparisons, and statistical process control methodologies.

Responsibilities

Own detection-to-resolution for data quality and abnormality issues in Databricks, including alert coverage, triage, routing, SLAs, root-cause analysis, and closure.
Ensure data quality and abnormality checks remain current as pipelines, models, and tables change; establish standards and review cadence to prevent silent drift.
Report data quality health and recurring failure patterns to stakeholders.
Define and maintain metric definitions, terminology, calculations, dimensions, and measurement standards across functions.
Establish metric certification standards and governance gates for metrics included in official reporting.
Document and maintain metric standards in the organization’s internal tool.
Mentor analysts, data engineers, and BI developers to promote sustainable governance practices.
Work with analytics engineers to architect and govern Databricks Gold-layer data models, including certified models with embedded data quality and abnormality checks.
Create metric views and maintain data lineage.
Drive tiered dataset assessment frameworks that evaluate completeness, accuracy, governance maturity, and automation readiness to determine safe levels of AI autonomy.
Translate certified metrics into natural-language-queryable experiences.
Lead or contribute to enterprise trusted data foundation and supply chain data governance initiatives.
Own and maintain KPI taxonomy and relationships between executive metrics, operational drivers, and root-cause indicators.
Develop and govern enterprise performance data models, standardized definitions, time grains, dimensional hierarchies, and reporting structures across supply chain domains.
Lead master data governance across product, supplier, customer, and compliance domains.
Establish target and threshold management processes that support cascading business objectives, seasonal adjustments, and planning updates.
Drive alignment on metric definitions, reporting standards, and measurement methodologies across business and technology teams.
Serve as a data governance subject matter expert in architecture reviews.