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2 месяца назад

VP, Business Data Delivery (Fintech)

240 000 - 270 000$
Формат работы
hybrid
Тип работы
fulltime
Грейд
c_level
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
VP, Business Data Delivery (Fintech): Building trusted, business-ready data products and customer data capabilities for marketing, lending, credit risk, fraud, operations, deposits, and compliance with an accent on data product strategy, customer activation, analytics, and AI enablement. Focus on leading data engineering, analytics engineering, data product management, and data science organizations, establishing governance and quality standards, and translating executive priorities into measurable business outcomes.

Location: San Francisco, United States; hybrid work model with in-office attendance required on Tuesdays, Wednesdays, and Thursdays; remote placement is not considered. Primarily Pacific Time, with flexibility across time zones when necessary. Relocation is offered based on actual job level.

Salary: $240,000–$270,000 target base salary annually, plus potential equity and annual bonus.

Company

hirify.global provides focused financial products and mobile-first experiences designed to help millions of Americans improve their financial health.

What you will do

  • Define and execute the roadmap for business-facing data products supporting marketing, lending, credit risk, fraud, operations, deposits, and compliance.
  • Lead Data Engineering, Analytics Engineering, Data Product Management, and Data Science delivery organizations.
  • Own customer data strategy, including customer and behavioral data integration, Customer Data Platform initiatives, identity resolution, and downstream activation.
  • Define business-facing analytics, AI enablement, self-service data products, and machine learning data capabilities.
  • Establish data quality, certification, testing, monitoring, governance, and delivery standards.
  • Build a data-driven culture and advise executive leadership on data strategy, customer data, analytics, and AI opportunities.

Requirements

  • 13+ years of experience in data engineering, analytics engineering, data product management, or related technology, including 10+ years leading and developing teams.
  • 5+ years leading large-scale data products, Customer Data Platforms, analytics organizations, or business-facing data delivery functions in a public cloud environment.
  • Experience delivering data products for customer experiences, marketing activation, credit decisioning, fraud detection, operations, and business intelligence.
  • Strong understanding of modern data architectures, customer data platforms, analytics ecosystems, and data product operating models.
  • Experience with lakehouse platforms such as Databricks, transformation tooling such as dbt, BI platforms such as Tableau, and cloud-native data architectures.
  • Experience with advanced analytics, machine learning, AI-enabled business capabilities, and highly regulated industries; bachelor's degree or equivalent experience.

Nice to have

  • Experience in both high-growth organizations and large-scale enterprises.
  • Knowledge of consumer financial products, lending, deposits, fraud, risk, collections, or personal financial management.
  • Experience with AWS, enterprise AI enablement, and modern data product transformations.
  • Proven ability to attract, hire, and develop technical and product talent.

Culture & Benefits

  • Mission-driven work focused on fairness, simplicity, innovation, and improving financial health.
  • Medical, dental, and vision plans for employees and families.
  • 401(k) matching, health and wellness programs, and flexible time off for salaried employees.
  • Up to 16 weeks of paid parental leave.
  • Travel to hirify.global offices or other locations as needed.

Hiring process

  • Interviews may be recorded, transcribed, and summarized using AI tools for select roles and locations.
  • Candidates may opt out of recording, transcription, and summarization before scheduled interviews.

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