Analytics Engineer, Freshpaint

• We’re looking for a Analytics Engineer who thinks in systems, not dashboards — someone who sees messy, fragmented data and instinctively starts designing the structure that makes it usable, reliable, and scalable
• You’re at your best when you’re building foundations that others depend on. You don’t just answer questions — you eliminate the need to ask them twice. You care deeply about data quality, consistency, and trust, and you hold a high bar for how data is modeled, documented, and used across a company
• You operate with leverage in mind. Instead of reacting to ad hoc requests, you build durable data assets that scale across teams and reduce friction over time. You’re comfortable working across Product, Engineering, and GTM, translating real-world problems into clean, well-defined data models
• You’re equally comfortable going deep in SQL/dbt as you are stepping back to define standards, governance, and long-term architecture. And most importantly, you measure success not by output, but by how much faster and more confidently the business can move because of your work
• 7+ years of experience in analytics engineering, data engineering, or business intelligence roles
• 3+ years of hands-on dbt experience building scalable, production-grade data models
• Deep SQL expertise and strong dimensional modeling fundamentals
• Experience working with modern data stacks (Snowflake, Fivetran, Looker)
• Experience supporting experimentation, predictive analytics, anomaly detection, or other advanced use cases
• Proven ability to implement governance practices and data quality controls
• Strong cross-functional collaboration skills; you translate technical complexity into business clarity
• Strong business acumen: you connect data architecture decisions directly to growth, product strategy, and revenue impact
• Comfort operating in ambiguity and proactively defining high-leverage initiatives

Desirable

• Freshpaint relies on data to drive product decisions, growth strategy, and customer outcomes — and as we scale, the need for a unified, reliable data foundation becomes critical
• In this role, you’ll architect and own that foundation
• You’ll design the unified data model that powers how teams measure performance, run experiments, and make decisions. You’ll build scalable dbt models in Snowflake, establish standards for how data is defined and governed, and create the analytics layer that enables self-serve insights and advanced use cases
• Your work will reduce metric fragmentation, eliminate ambiguity, and increase trust in data across the company. By turning data into a consistent, reliable system, you’ll enable teams to move faster, focus on higher-leverage work, and make better decisions with confidence
• Design and own the unified data model in Snowflake using scalable, production-grade dbt models
• Build analytics-ready datasets that serve as the single source of truth for KPIs and decision-making
• Establish modeling standards, metric definitions, and governance frameworks that scale with the company
• Partner with Product and Engineering to ensure reliable event instrumentation and high-quality upstream data
• Develop datasets that support experimentation, growth analysis, and advanced analytics use cases
• Build and maintain ingestion pipelines (e.g., Fivetran) to support new strategic data sources
• Create scalable data marts and Looker dashboards that enable self-serve analytics across teams
• Translate complex data into clear, actionable insights that influence product and go-to-market decisions
• Implement testing, monitoring, and anomaly detection to ensure data reliability and trust
• Reduce ad hoc work by building durable, reusable data assets that increase leverage across the organization