Head of Data

Data Strategy & Leadership
●    Define and execute HappyCo’s overall data strategy aligned with company and product goals
●    Establish the roadmap for analytics, machine learning, and data platform evolution
●    Collaborate with Product and Engineering leadership to identify high-value opportunities for data-driven insights and AI features
●    Build and mentor a small data team including data engineers and analysts

Data Unification & Canonical Data Model
●    Design and implement a canonical entity model that connects data across operational systems
●    Lead the development of HappyCo’s property graph / knowledge layer, linking entities such as businesses, properties, units, inspections, work orders, and maintenance performance
●    Develop entity resolution approaches using deterministic rules, fuzzy matching, geospatial matching, and machine learning where appropriate
●    Ensure that canonical entities are reliable and usable across analytics, reporting, and product systems

Data Platform & Architecture
●    Oversee the architecture and evolution of HappyCo’s data platform, including the data warehouse, pipelines, and transformation layers
●    Guide development of scalable data ingestion and transformation pipelines using tools such as BigQuery, Databricks, Dataflow, and Pub/Sub
●    Establish best practices for data quality, lineage, and governance
●    Ensure data infrastructure supports both analytical workloads and product-facing APIs

Analytics & Insights
●    Enable internal teams with reliable analytics and insights derived from unified data
●    Move the organization beyond dashboards toward insight generation and recommendations
●    Develop benchmark metrics and analytical models that help customers understand performance and opportunities for improvement
●    Support the creation of self-service analytics capabilities across the company

Machine Learning & AI Enablement
●    Prototype and implement predictive models that leverage unified data sets
●    Prepare datasets and feature pipelines for machine learning workflows
●    Enable AI product capabilities including agentic workflows and data-driven recommendations
●    Ensure the company’s data architecture supports retrieval systems and LLM-powered applications

Hands-On Technical Execution
●    Contribute directly to data modeling, analytics, and ML development
●    Work closely with the Data Engineer to implement pipelines and transformations
●    Prototype analytical models and AI-enabled features in collaboration with Product

Required Experience
●    8+ years of experience working in data science, data engineering, or analytics roles
●    Experience designing data architectures and data models for complex operational systems
●    Strong experience working with data warehouses and distributed data processing systems
●    Hands-on experience building analytical models or machine learning systems
●    Demonstrated ability to translate business questions into data-driven solutions
●    Experience working cross-functionally with product and engineering teams

 

Technical Skills
●    Strong proficiency in SQL and Python
●    Experience with modern data platforms (e.g., BigQuery, Snowflake, Databricks)
●    Experience building data pipelines and transformation workflows
●    Familiarity with machine learning workflows and model deployment
●    Experience with entity resolution, data modeling, or knowledge graph concepts is highly desirable

 

Leadership Qualities
●    Ability to operate effectively as both a strategic leader and hands-on contributor
●    Strong communication skills with both technical and non-technical stakeholders
●    Experience mentoring and developing data professionals
●    Comfort working in a fast-moving startup environment

A rare opportunity to shape the technical foundation of a growing SaaS platform during a major architectural transition.

High-impact role with visibility and influence across engineering and product leadership.

Collaborative engineering culture that values clarity, pragmatism, and continuous learning.

Competitive compensation, benefits, and flexible work arrangements.

First 3 Months
●    Develop a clear data strategy and roadmap aligned with product and engineering priorities
●    Begin implementation of the canonical entity model and property graph
●    Establish reliable mappings across key operational systems
●    Identify high-impact analytical opportunities using unified data

 

First 9 Months
●    Deliver the foundational property graph / canonical entity layer
●    Enable internal teams with improved analytics and benchmark insights
●    Implement initial predictive models or AI-driven features using unified data
●    Reduce ad hoc data requests through improved data models and analytics capabilities

 

Long Term
●    Establish HappyCo’s unified data platform as the foundation for product insights and AI capabilities
●    Build a high-performing data team including engineers and analysts
●    Enable AI-powered workflows and customer-facing insights driven by proprietary data