Key skills
Analytics engineeringData engineeringData scienceCustomer-facing reportingDashboard developmentModern data stack technologiesdbtSnowflakeSQLPythonLookerOmniData modelingStar schema designSnowflake schema designData governanceData quality frameworksAnalytics security best practicesMachine learningForecastingPersonalizationRecommendationsAnomaly detectionMachine LearningMLAnalyticsProduct ManagementCommunicationCollaboration
About this role
Boulevard is a client experience platform for appointment-based, self-care businesses, empowering customers to enhance their client interactions. The Staff Analytics Engineer will architect and lead the analytics foundation, focusing on data ecosystems, visualization, and machine learning applications to drive data-driven decision-making across the company.
Responsibilities:
- 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