Vice President of Data

Double Good•Chicago, IL

12h•Hybrid

About The Position

The VP of Data will lead the enterprise data organization to deliver trusted, product-oriented data assets that power analytics, visibility, and decision-making across Double Good—enabling the business to grow faster with confidence and exploration in its data. This role serves every function across Double Good that relies on data to operate and make decisions. The VP of Data is accountable for ensuring that marketing, sales, operations, finance, customer success, Product and Technology, and executive leadership all have access to reliable, timely, and well-governed data products tailored to their needs. The data organization under this role operates as an internal product team, delivering a portfolio of data products and platform services that span the full data lifecycle: Ingestion Services: Managed pipelines that reliably move data from application databases, third-party SaaS platforms, and event streams into the data warehouse. Data Warehouse & Modeling Services: Curated, tested, and documented dimensional models that organize raw data into business-ready structures. Semantic Layer & Metrics Services: Governed metric definitions, LookML models, and BI frameworks that ensure a single source of truth across all reporting. Platform Services: A reliable, performant, and cost-efficient data platform (Snowflake, dbt, orchestration, observability) available to all data consumers. Data Governance Services: Standards, policies, cataloging, lineage, and access controls that protect data quality and regulatory compliance. This is a senior leadership position that carries both strategic and operational accountability: Manages a team of 4 - 8 direct reports spanning analytics engineering, platform engineering, semantic layer development, and data product management, with potential to grow as the organization scales. Owns the data platform budget, including cloud warehouse costs, tooling licenses, and contractor spend. Has decision-making authority over data architecture, tooling selection, data modeling standards, and team structure within the data organization. Operates as a peer to other senior technology leaders and partners directly with business unit heads to align data investments with functional priorities. Reports to the CTO and participates in technology leadership forums, contributing to company-wide technology strategy and investment decisions.

Requirements

10+ years of progressive experience in data engineering, analytics engineering, or data platform leadership, with at least 5 years in a senior management or VP-level role.
Deep expertise in modern data stack technologies: cloud data warehouses (Snowflake preferred), transformation frameworks (dbt preferred), and BI/semantic layer platforms (Looker/LookML preferred).
Track record of building and leading data teams that operate with a product mindset—delivering governed, documented, consumer-oriented data products.
Strong understanding of dimensional modeling, data warehouse architecture patterns (star schema, OBT), and data governance frameworks.
Experience with AWS cloud infrastructure, data pipeline orchestration, and CDC/streaming technologies.
Demonstrated ability to partner cross-functionally with business stakeholders and translate business needs into scalable data solutions.
Experience operating in a SOC 2 compliant environment and understanding of data security, privacy, and access control best practices.
Excellent communication skills with the ability to present data strategy and trade-offs to executive leadership.

Nice To Haves

Experience in e-commerce, marketplace, or platform business models where an understanding of multi-sided user journeys (organizers, sellers, buyers) is valuable.
Familiarity with product management methodologies applied to internal data products and platforms.
Experience managing data platform costs and optimizing cloud spend.
Background in building analytics solutions that support both operational reporting and strategic decision-making.

Responsibilities

Data Strategy & Product Management Define and execute the company data strategy, positioning data as a product portfolio that serves internal consumers across marketing, sales, operations, finance, technology and product, and executive leadership.
Own the data product roadmap, prioritizing purpose-built data products (e.g., Unit Economics, Fundraiser Performance, Marketing Performance, Seller Engagement) over source-system-oriented models.
Establish product management practices within the data organization, including stakeholder discovery, requirements gathering, SLA definitions, and iterative delivery.
Partner with the CTO and executive team to align data investments with business objectives and growth strategy.
Data Ingestion & Integration Oversee all data ingestion pipelines, ensuring reliable extraction from source systems (application databases, third-party SaaS platforms, event streams) into the data warehouse.
Evaluate and manage CDC streaming and ETL/ELT tooling, making build-vs-buy decisions that balance cost, reliability, and latency requirements.
Establish data contracts and integration standards with application engineering teams to ensure upstream changes don’t break downstream analytics.
Data Organization & Architecture Own the enterprise data warehouse architecture, including dimensional modeling (star schema), staging layers, business logic centralization, and consumption layer design.
Drive the evolution from domain-centric source models to curated, purpose-built analytical data products with clear ownership and documentation.
Establish and enforce data governance standards including data quality, lineage, cataloging, access controls, and compliance (SOC 2, privacy regulations).
Define naming conventions, transformation standards, and testing frameworks to ensure consistency and reliability across the data platform.
Platform Engineering Manage and optimize the modern data stack, including cloud data warehouse (Snowflake), transformation tooling (dbt), orchestration, and data observability.
Ensure platform reliability, performance, and cost efficiency as data volumes and user demands scale.
Evaluate and implement new technologies that improve data freshness, pipeline observability, and developer experience for the data team.
Partner with infrastructure and security teams to maintain SOC 2 compliance and data protection standards across all data systems.
Presentation & Semantic Layer Engineering Own the semantic layer and BI platform strategy, ensuring business users have access to consistent, governed metrics and dimensions across all reporting surfaces.
Lead the design and engineering of LookML models, Explores, and dashboards (or equivalent BI tooling) that deliver self-service analytics capabilities to the business.
Establish a metrics framework that serves as the single source of truth for key business measures, eliminating conflicting definitions across teams.
Drive adoption of data products across the organization through training, documentation, and stakeholder enablement.
Team Leadership & Organizational Development Build, lead, and develop a high-performing data team spanning analytics engineering, platform engineering, semantic layer development, and data product management.
Attract and retain top data talent, fostering a culture of ownership, craftsmanship, and business partnership.
Establish team structures, career ladders, and operating rhythms that support both individual growth and organizational scalability.
Manage vendor relationships and budgets for the data platform portfolio.

Benefits

Double Good offers competitive benefits including medical, dental and vision coverage with plans that can fit each teammate’s needs.
We offer immediate vesting in our 401k plan, paid time off, company-paid leaves and other perks including a Popcorn Allowance (yup, free popcorn!).

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