Boulevard is a company that provides a client experience platform for appointment-based self-care businesses. They are seeking a Staff Analytics Engineer to architect and lead the analytics foundation, managing data visualization, advanced machine learning capabilities, and systems for data-driven products and decision-making across the company.
Responsibilities:
- Architect and lead the analytics foundation powering Boulevard’s data ecosystem and data products
- Own our analytical platform, data visualization, advanced machine learning capabilities, and the systems that enable data-driven products and decision-making across the company
- Drive complex, high-impact data initiatives that enhance product performance and customer experience through actionable insights and robust analytical frameworks
- Design, build, and maintain foundational data models that serve as the single source of truth for analytics across both internal and external stakeholders
- Partner with Product, Engineering, and Analytics teams to scope and deliver new initiatives, develop analytics features, and create data-driven customer experiences
- Develop frameworks, tools, and workflows that enhance efficiency and scalability, ensuring high standards of data quality, consistency, and performance
- Translate business requirements into scalable data models, dashboards, and analytical tools
- Proactively identify opportunities for anomaly detection, predictive analytics, recommendations, forecasting, and AI-driven innovation
- Leverage modern analytics and development tools to deliver measurable business value quickly—while maintaining long-term scalability and maintainability
- Collaborate with Product Management and Engineering to deliver robust customer-facing reporting, dashboards, and analytics features
- Design and implement secure, performant Snowflake data sharing solutions that empower customers to access and leverage data safely and efficiently
- Oversee data visualization platforms, optimizing data models and query performance to deliver fast, reliable, and intuitive analytics experiences
- Develop and deploy machine learning solutions for recommendations, forecasting, anomaly detection, and predictive insights that enhance product intelligence
- Lead complex data initiatives by transforming ambiguous business needs into scalable architectures, pipelines, and analytical models that deliver impact
- Partner with Product Management, Product Engineering, and Analytics to understand requirements and deliver analytics platform capabilities for both external and internal stakeholders
- Drive key semantic modeling design decisions that balance current reporting needs with future scalability and adaptability
- Design, train, and operationalize ML models for use cases such as forecasting, personalization, recommendations, and anomaly detection
- Integrate these models into production pipelines and ensure continuous improvement through experimentation and monitoring
- Establish and enforce best practices for data governance, cataloging, lineage tracking, and quality assurance across the analytics and ML ecosystem
Requirements:
- Bachelor's degree or higher in Computer Science, Information Technology, Data Science, or a related discipline
- 8+ years of professional experience in the data domain — including roles such as Analytics Engineer, Data Engineer, Data Scientist, or similar
- Proven track record of delivering customer-facing reporting, dashboards, and analytics capabilities in partnership with Product teams
- Deep expertise with modern data stack technologies such as dbt, Snowflake, SQL, Python, and Looker/Omni
- Strong understanding of modular and reusable data modeling best practices (e.g., star and snowflake schema design)
- Comprehensive knowledge of data governance, data quality frameworks, and analytics/security best practices
- Excellent problem-solving, communication, and cross-functional collaboration skills, with experience working on global teams