Staff Data Engineer

Boulevard

20h•Remote

About The Position

Boulevard is seeking a Staff Data Engineer to architect and lead the data foundation powering Boulevard’s data products. This role will own the data platform, visualization, advanced machine learning capabilities, and the systems that enable data-driven products and decision-making across the company. Reporting to the Director of Data Engineering, the Staff Data Engineer will play a critical role in architecting, designing, developing, and maintaining the data ecosystems and analytics capabilities that power customer-facing products. This role will drive complex, high-impact data initiatives that enhance product performance and customer experience through actionable insights and robust analytical frameworks. This senior technical role demands extensive expertise in data architecture, analytics engineering, and practical machine learning applications.

Requirements

Bachelor’s degree or higher in Computer Science, Information Technology, Data Science, or a related discipline
7+ years of professional experience in Data Engineering
Proven track record of delivering data products, data platform capabilities in partnership with Product teams
Deep expertise with modern data stack technologies: DBT, Snowflake, SQL, Python, and BI tools like 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

Responsibilities

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.