Role overview

Staff Data Engineer

Requirements and responsibilities

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Domains of Ownership

  • Data Architecture - Design, build, and maintain foundational data models that serve as the single source of truth for analytics across both internal and external stakeholders.
  • Cross-Functional Collaboration - Partner with Product, Engineering, and Analytics teams to scope and deliver new initiatives, develop analytics features, and create data-driven customer experiences.
  • Scalable Data Products - Develop frameworks, tools, and workflows that enhance efficiency and scalability, ensuring high standards of data quality, consistency, and performance.
  • AI Innovation & Actionable Insights - 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.Impact-Focused Solutions - Leverage modern analytics and development tools to deliver measurable business value quickly—while maintaining long-term scalability and maintainability.

Key Projects & Initiatives

  • Customer-facing Data Products: Collaborate with Product Management and Engineering to deliver robust customer-facing reporting, dashboards, and analytics features.
  • Snowflake Data Sharing - Design and implement secure, performant Snowflake data sharing solutions that empower customers to access and leverage data safely and efficiently.
  • Data Visualization & Performance Optimization - Oversee data visualization platforms, optimizing data models and query performance to deliver fast, reliable, and intuitive analytics experiences.
  • Machine Learning & AI Innovation - Develop and deploy machine learning solutions for recommendations, forecasting, anomaly detection, and predictive insights that enhance product intelligence.

What You'll Do Here

  • Technical Architecture - Lead complex data initiatives by transforming ambiguous business needs into scalable architectures, pipelines, and analytical models that deliver impact.
  • Cross-Functional Collaboration: Partner with Product Management, Product Engineering, and Analytics to understand requirements and deliver analytics platform capabilities for both external and internal stakeholders.
  • Data Modeling & Design: Drive key semantic modeling design decisions that balance current reporting needs with future scalability and adaptability.

What You'll Need to Thrive

  • 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

Details

  • ✨ We’ve got you covered with a 401(k) match plus dental, medical, vision, and life insurance.
  • 🏝 Take a break whenever you need with our flexible vacation day policy.
  • 🖥 Fully remote so you can choose where you want to work. You’ll receive a work from home stipend every month.
  • 💚 Family planning resources and specialized support programs.
  • 🔮 Equity: get ahead on the ground floor and grow with Boulevard.
  • 💅 Boulevard Bucks Learning and Development program allows employees to explore businesses in the market we serve.
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Browse stack
FocusData EngineeringRole area
Seniority signalSeniorCandidate level
StackPython, Snowflake, SQLPrimary skills
Location1 accepted countryEligibility

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