Director of Data
Role details
Job location
Tech stack
Job description
B-Stock is seeking a strategic and hands-on Director of Data to lead our Analytics, Data Engineering, and Data Science functions. This leader will unify our data organization into a high-performing Center of Excellence and play a key role in enabling AI-driven product innovation across bstock.com.
This is a highly visible leadership role that partners closely with Engineering, Product, Marketing, and Executive Leadership to ensure data drives measurable business impact.
WHAT YOU WILL DO?
Lead and Scale the Data Organization
- Oversee Analytics, Data Engineering, and Data Science teams.
- Build and execute a forward-looking Data & AI strategy aligned to company goals.
- Hire and grow high-performing talent, future AI/LLM specialists.
- Establish a culture of technical excellence, accountability, and measurable business impact.
Drive Business & Product Analytics
- Own business intelligence and analytics platforms including Tableau, GA4, and Amplitude.
- Standardize company-wide metrics and ensure trusted, actionable reporting.
- Enable scalable self-serve analytics and experimentation frameworks.
- Partner with Marketing and Product teams on attribution, growth analytics, and product insights.
Build Scalable Data Infrastructure (GCP-Based)
- Lead the architecture, optimization, and scalability of data pipelines and warehouse infrastructure within Google Cloud Platform (GCP).
- Leverage GCP data services (e.g., BigQuery, Dataflow, Pub/Sub, Cloud Storage, Composer, Dataproc) to build reliable, performant systems.
- Ensure strong data quality, governance, security, and cost optimization practices.
- Define and manage SLAs for production data systems.
- Improve observability and monitoring across the data stack.
Advance Data Science, ML & AI Capabilities
- Lead the development and productionization of ML models that improve marketplace performance.
- Leverage GCP AI/ML services (e.g., Gemini, AutoML, model deployment and monitoring tools) to accelerate experimentation and advance analytical capabilities.
- Establish best practices for experimentation, model lifecycle management, and MLOps.
WHAT SUCCESS LOOKS LIKE?
- A unified and high-performing Data organization.
- Trusted, standardized metrics across the company.
- Scalable, reliable GCP-based data infrastructure supporting business growth.
- AI/ML models successfully drive into the data driven product features.
- Clear data-driven insights influencing executive decision-making.
Requirements
- 10+ years of experience in Analytics, Data Engineering, or Data Science.
- 5+ years leading multi-functional data teams.
- Strong experience owning both analytics and data infrastructure in a SaaS environment.
- Deep experience with Google Cloud Platform (GCP), including:
- BigQuery and modern cloud data warehousing
- Data pipeline and orchestration tools (e.g., Dataflow, Pub/Sub, Composer)
- Cloud-based ML platforms (e.g., Vertex AI)\
- Infrastructure, cost management, and performance optimization in GCP
- Experience production-izing ML models in real-world applications.
- Strong familiarity with BI tools (Tableau, Power BI or similar) and product analytics tools (Amplitude, GA4 or similar).
- Experience working cross-functionally with Product and Engineering leaders.
NICE TO HAVE
- Marketplace or two-sided platform experience.
- Experience scaling data organizations in high-growth SaaS companies.
Benefits & conditions
The pay rate for this role will range between $250,000 to $275,000, per annum. We consider many factors when determining salary offers, such as the applicant's work experience, education and training, skills, market data, and internal equity., * Competitive compensation packages, including bonus and options
- Medical, Dental, and Vision benefits
- Paid Time Off, telecommuting, and matching 401(K)
- Support for continuing education
- Team offsites, social events, and extracurricular activities are a staple
- Snacks, drinks, and the occasional box of donuts