Supio
Data Engineer
Seattle Hybrid
Sponsorship not specified$185k-$220kDetected 34 days ago
Data EngineeringData ScienceLLMsAgentic AILeadershipCommunicationCollaboration
About the role
- You'll work closely with senior engineering and leadership across the company, sitting at the intersection of data infrastructure, AI, and business strategy.
- Qualifications Experience: 4+ years in data engineering or data science, with a track record of owning and delivering complex data projects end-to-end as an individual contributor.
Responsibilities
- Establish Data Foundations: Build the data infrastructure needed to deeply understand agent behavior, usage patterns, and performance-turning raw signals into actionable intelligence that informs product and business decisions.
- Build Agent Evaluation Infrastructure: Design and implement structured evaluation frameworks for Supio's AI agents, creating the measurement systems that enable continuous improvement of our core product.
- Solve High-Impact Business Problems: Identify and build systems that address Supio's most critical data challenges, driving outcomes that matter to the business rather than producing routine reports.
- Shape Data Strategy: Partner with senior engineering and leadership to define where data creates the most leverage, elevating the function beyond basic analytics toward real business impact.
- This isn't a role for someone who waits for requirements; it's for an independent thinker who seeks out cross-functional peers for problems worth solving and then builds the systems to solve them.
- If you're energized by building from the ground up and making ambiguous problems concrete, this is the role for you.
- Build the data infrastructure needed to deeply understand agent behavior, usage patterns, and performance-turning raw signals into actionable intelligence that informs product and business decisions.
- Identify and build systems that address Supio's most critical data challenges, driving outcomes that matter to the business rather than producing routine reports.
- Partner with senior engineering and leadership to define where data creates the most leverage, elevating the function beyond basic analytics toward real business impact.
- Proven track record driving projects from initial scoping through delivery without requiring close direction; you own outcomes, not just tasks.
Requirements
- 4+ years in data engineering or data science, with a track record of owning and delivering complex data projects end-to-end as an individual contributor.
- Strong ability to communicate technical concepts and findings to non-technical stakeholders, including senior leadership.
Skills
- Communication: Strong ability to communicate technical concepts and findings to non-technical stakeholders, including senior leadership.
- Collaboration: Comfortable working across engineering, product, and leadership teams in a fast-moving startup environment.
- Familiarity with LLMs, AI agents, or evaluation frameworks for generative AI systems.
- Background that spans product management and data engineering, with the ability to bridge both worlds.
- Exposure to legal tech or other complex verticals.
Compensation
- $185,000 - $220,000 annually
Benefits
- Compensation As an early-stage startup, we offer a competitive compensation package that includes base salary, meaningful equity, and benefits.
- Equity grants are designed to ensure employees share in the long-term success and upside of the company.
Company info
- Analyze User Behavior: Investigate how customers interact with Supio's platform, comparing natural language input patterns against traditional click-based behavior to surface insights that drive product strategy.
- Who we're looking for We're looking for a Data Engineer who brings intellectual curiosity and genuine drive to understand the business and product - not just the data.
- Investigate how customers interact with Supio's platform, comparing natural language input patterns against traditional click-based behavior to surface insights that drive product strategy.
This listing is sourced directly from Supio's careers page and normalized into a canonical job model.