Vensure Employer Solutions
Senior Vice President of Enterprise Data - AZ - On site
Vensure Employer Solutions, Chandler, Arizona, United States, 85249
Senior Vice President of Enterprise Data - AZ - On site
Join to apply for the Senior Vice President of Enterprise Data - AZ - On site role at Vensure Employer Solutions.
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—to drive a cultural shift toward data reliability, speed, and reuse at scale.
Responsibilities
Unify Vensure HR data into a single data lake/lakehouse across all platforms and subsidiaries, with robust governance and security.
Industrialize data readiness—compile, cleanse, standardize, and productize data for easy consumption by daily reporting, self‑service analytics, and AI/ML training.
Define and execute the enterprise data architecture (data lake/lakehouse, streaming, MDM, metadata, lineage, quality) aligned to business OKRs.
Build high‑throughput, cost‑efficient pipelines (batch/streaming) with automated testing, observability, and data SLAs.
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.
Mentor teams across data engineering, architecture, governance, and analytics; recruit and develop top talent.
Select and govern platform standards (e.g., Azure/AWS; Databricks/Snowflake/Synapse; ClientSpace; dbt/Airflow; Power BI/Tableau).
Implement gold/semantic layers for trusted daily and intraday reporting.
Establish data product ownership, versioning, and change‑management for stable AI/ML training sets.
Create incident response and data quality playbooks with measurable remediation timelines.
Partner with stakeholders to deliver value and realize business outcomes.
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 experience with PEO/HR Tech, payroll, benefits, workers’ comp, or insurance data domains (HRIS, time & attendance, claims, underwriting, policy/billing).
Success Metrics (Illustrative)
90 days: Target state architecture & migration plan; baseline data inventory, lineage, and quality; staffing and operating model finalized.
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‑to‑dataset 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 & Certifications
None
Physical Demands
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.
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
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
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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—to drive a cultural shift toward data reliability, speed, and reuse at scale.
Responsibilities
Unify Vensure HR data into a single data lake/lakehouse across all platforms and subsidiaries, with robust governance and security.
Industrialize data readiness—compile, cleanse, standardize, and productize data for easy consumption by daily reporting, self‑service analytics, and AI/ML training.
Define and execute the enterprise data architecture (data lake/lakehouse, streaming, MDM, metadata, lineage, quality) aligned to business OKRs.
Build high‑throughput, cost‑efficient pipelines (batch/streaming) with automated testing, observability, and data SLAs.
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.
Mentor teams across data engineering, architecture, governance, and analytics; recruit and develop top talent.
Select and govern platform standards (e.g., Azure/AWS; Databricks/Snowflake/Synapse; ClientSpace; dbt/Airflow; Power BI/Tableau).
Implement gold/semantic layers for trusted daily and intraday reporting.
Establish data product ownership, versioning, and change‑management for stable AI/ML training sets.
Create incident response and data quality playbooks with measurable remediation timelines.
Partner with stakeholders to deliver value and realize business outcomes.
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 experience with PEO/HR Tech, payroll, benefits, workers’ comp, or insurance data domains (HRIS, time & attendance, claims, underwriting, policy/billing).
Success Metrics (Illustrative)
90 days: Target state architecture & migration plan; baseline data inventory, lineage, and quality; staffing and operating model finalized.
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‑to‑dataset 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 & Certifications
None
Physical Demands
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.
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
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
#J-18808-Ljbffr