Sobre esta vaga de Staff Data Engineer na Artisan
About Artisan
We're building AI employees. Not chatbots. Not copilots. Autonomous digital workers that do real jobs.
Our first, Ava, is an AI BDR used by hundreds of companies. She researches leads, writes and sends emails in a customer's voice, runs multi-step outbound sequences, manages her own deliverability infrastructure, self-optimizes over time, and handles objections and meeting booking. She's not a tool someone uses. She's a teammate.
We're a YC W24 company, have raised $35M+ from investors including Y Combinator, and are at $8M+ ARR. Right now we're building Ava 2.0, a step change in what an AI employee can do. The engineering problems are hard and the surface area is enormous.
Role overview
You'll be the first Data Engineer on the Artisan team! We're managing a database of hundreds of millions of leads and creating real-time intent signals which monitor data fields for those leads. You'll own everything data-related at Artisan.
Design, build, and maintain scalable data pipelines that process and transform large volumes of structured and unstructured data
Manage ingestion from third-party APIs, internal systems, and customer datasets
Develop and maintain data models, data schemas, and storage systems optimized for ML and product performance
Collaborate with ML engineers to prepare model-ready datasets, embeddings, feature stores, and evaluation data
Implement data quality monitoring, validation, and observability
Work closely with product engineers to support new features that rely on complex data flows
Optimize systems for performance, cost, and reliability
Contribute to early architecture decisions, infrastructure design, and best practices for data governance
Build tooling that enables the entire team to access clean, well-structured data
Location: San Francisco, New York, or Remote USA
Team: Engineering
Reports to: CPTO, Sam Stallings
Who you are
3+ years of experience as a Data Engineer
Proficiency in Python, SQL, and modern data tooling (dbt, Airflow, Dagster, or similar)
Comfort working in fast, ambiguous environments
Experience designing and operating ETL/ELT pipelines in production
Experience with cloud platforms (AWS, GCP, or Azure)
Familiarity with data lakes, warehouses, and vector databases
Experience integrating APIs and working with semi-structured data (JSON, logs, event streams)
Strong understanding of data modeling and optimization
Bonus: experience supporting LLMs, embeddings, or ML training pipelines
Bonus: startup experience
Interview process
Introductory chat with our recruiter
1 hour technical interview with an engineer
1 hour technical interview with an engineer
30-minute interview with Sam, our CPTO
15-minute culture and values interview with Jaspar, our CEO
Our culture and values
Founder mindset. Everyone acts like an owner: take initiative, think big, challenge ideas, and push for 10× outcomes
Obsessed with impact. We apply the 80/20 rule, kill sunk costs quickly, and focus on what actually moves the needle
Customer-first, always. Every decision is made with the customer experience at the center
High standards, every detail. Quality matters in everything we ship, from product and code to copy and design
Clear, direct communication. We value candor, fast responses, and feedback
Winning team energy. We bring positive vibes, low ego, zero drama, and genuinely enjoy building together
