Senior Vice President of Enterprise Data - AZ - On site

F3nomenal; Chandler (AZ); On-site; USD 250,000 - 350,000; Full time

Benefits offered by this job

Health Insurance

401(k) Match

Paid Time Off

Other Benefits

Job summary

Vensure Employer Solutions seeks a Senior Vice President of Enterprise Data to own the end-to-end data strategy, architecture, and governance across HR, payroll, and insurance. You will unify data lakehouse platforms, drive AI-ready datasets, and lead cross-functional teams in a fast‑paced, global environment.

As a senior executive, you will mentor data engineering, governance, and analytics teams, partnering with stakeholders to translate technical roadmaps into business outcomes and measurable

Qualifications

• BS/MS in Computer Science, Data/Software Engineering, Information Systems or related.
• MBA or executive experience preferred.
• 15+ years in data architecture, engineering, analytics.
• Experience leading large multi-brand data organizations.

Responsibilities

• Unify data across platforms into a lakehouse with governance.
• Define enterprise data strategy, architecture, and governance.
• Lead data engineering, analytics, and AI readiness initiatives.
• Mentor teams and partner with senior stakeholders to drive ROI.

Skills

Executive leadership

Data architecture

Cloud data platforms

Stakeholder communication

Education

BS in CS/Engineering

MBA preferred

Tools

Azure

Databricks

Snowflake

Python/SQL

Airflow

Job description

We are a proud work-from-office company. If you're ready to work on-site in a dynamic, global company, we'd love to hear from you.

About Us

Vensure Employer Solutionsis the largest privately held organization in the HR technology and service sector, providing a comprehensive portfolio of solutions, including HR/HCM technology, managed services, and global business process outsourcing (BPO). The company and its service providers collectively serve over 95,000 businesses and process over $135B in annual payroll. As a "One Employer Solution” headquartered in Chandler, Arizona, Vensure helps thousands of businesses streamline and grow their operations with custom strategies that benefit both employers and employees. Find out more by visiting www.vensure.com.

Position Summary

The Senior Vice President of Enterprise Data is an executive leader and main data architect responsible for operationalizing a unified, enterprise-grade data foundation that powers daily reporting, advanced analytics, and AI across our HR, payroll, and insurance businesses. The SVP will own the end-to-end data strategy—spanning architecture, engineering, and governance helping to drive a cultural shift toward data reliability, speed, and reuse at scale.

Essential Duties and Responsibilities

Top Priorities (First 12–18 Months)

1. Unify Vensure HR data into a single data lake/Lakehouse across all platforms and subsidiaries, with robust governance and security.
2. Industrialize data readiness—compile, cleanse, standardize, and productize data for easy consumption by daily reporting, self-service analytics, and AI/ML training.

Key Responsibilities

Data Strategy & Architecture

• Define and execute the enterprise data architecture (data lake/lakehouse, streaming, MDM, metadata, lineage, quality) aligned to business OKRs.
• Select and govern platform standards (e.g., Azure/AWS; Databricks/Snowflake/Synapse; ClientSpace; dbt/Airflow; Power BI/Tableau).

Data Engineering & Operations

• Build high-throughput, cost-efficient pipelines (batch/streaming) with automated testing, observability, and data SLAs.
• Implement gold/semantic layers for trusted daily and intraday reporting.
• Establish data product ownership, versioning, and change-management for stable AI/ML training sets.

Governance, Risk, & Compliance

• Implement data governance (catalog, lineage, access controls), privacy-by-design, and retention standards; ensure compliance with SOC 2, HIPAA where applicable, and state/federal employment data regulations.
• Create incident response and data quality playbooks with measurable remediation timelines.

People & Operating Model

• Mentor teams across data engineering, architecture, governance, and analytics; recruit and develop top talent.

Stakeholder Partnership & Value Realization

Knowledge, Skills, and Abilities

• Proven track record building enterprise data lakes/lakehouses and migrating disparate source systems to standardized models.
• Deep expertise in data modeling (3NF, star, data vault), MDM/reference data, metadata/lineage, and data quality frameworks.
• Hands‑on leadership with modern stacks: cloud data platforms (Azure preferred), Spark/Databricks or Snowflake, Python/SQL, orchestration (Airflow/dbt), streaming (Kafka/Event Hubs), CI/CD and IaC (Terraform), BI (Power BI/Tableau/Looker).
• Demonstrated success enabling daily operational reporting at scale and producing AI/ML‑ready datasets (feature stores, governance for model risk).
• Executive communication skills: able to set vision, influence senior stakeholders, and translate technical roadmaps into business outcomes.
• Industry plus: experience with PEO/HR Tech, payroll, benefits, workers' comp, or insurance data domains (HRIS, time & attendance, claims, underwriting, policy/billing).

Leadership & Operating Model

• Establish a federated‑to‑centralized model: central standards and platforms with domain‑aligned data product teams.
• Drive a culture of accountability with outcome‑based metrics, transparent roadmaps, and executive dashboards.

Success Metrics (Illustrative)

• 90 days: Target state architecture & migration plan; baseline data inventory, lineage, and quality; staffing and operating model finalized with SVP Analytics.
• 6 months: First unified domains in lakehouse (e.g., HR, payroll), certified daily KPI packs live, data SLAs operational; AI feature store v1.
• 12 months: 70%+ critical sources unified; daily reporting reliability >99%; time‑todataset reduced by 50%; 3+ AI initiatives trained on governed datasets.
• 18 months: Full run‑rate operating model; cost per query and pipeline efficiency improved; measurable ROI from analytics & AI programs.

Education & Experience

• BS/MS in Computer Science, Data/Software Engineering, Information Systems, or related; MBA or equivalent executive experience preferred.
• 15+ years progressive experience across data architecture, data engineering, and analytics; 7+ years leading large, multi‑disciplinary data organizations in complex, multi‑brand environments.

Required Licenses and/or Certifications

• None

Physical Demands

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.

• Frequently required to sit; occasionally required to stand and walk.
• Specific vision abilities required include close vision, color vision, and ability to adjust focus.
• Frequently required to talk and hear.
• Moderate concentration/intensity, which includes prolonged mental effort.

Disclaimer

The above job description is not intended to be an all‑inclusive list of duties and standards of the position. Incumbents will follow any other instructions, and perform any other related duties, as assigned by their supervisor.

This position is eligible for the following benefits:

• Health Insurance: Medical, dental, and vision coverage
• Retirement Plan: 401(k) with company match
• Paid Time Off: PTO, Holidays, Parental leave and Sick Leave provided as required by applicable state law
• Other Benefits: Life insurance, short term disability, long term disability, employee assistance program (EAP), flexible spending account (FSA), health savings account (HSA), Identity theft protection, critical illness, accident, cancer, hospital protection, legal and pet insurance.
• Additional Compensation: [e.g., signing bonus, commission structure] if applicable