We are looking for a high-caliber Data Engineer who can architect and scale the data systems that power our AI workflows. You’ll be responsible for building reliable data pipelines, integrating external APIs, maintaining clean and structured data models, and enabling the product and ML teams to iterate quickly.
You should thrive in ambiguous environments, enjoy wearing multiple hats, and be comfortable designing end-to-end data solutions with minimal direction.
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.
You’re a hands-on engineer who thrives in a fast-paced environment, enjoys autonomy, and takes ownership of problems from start to finish.
You translate technical complexity into clarity. You work well with ML, product, and GTM partners.
You can design elegant systems but default to shipping solutions that work and can be iterated on.
You care about clean pipelines, reproducibility, and data correctness.
3+ years of experience as a Data Engineer, ML Engineer, Backend Engineer, or similar.
Proficiency in Python, SQL, and modern data tooling (dbt, Airflow, Dagster, or similar).
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 or comfort working in fast, ambiguous environments.
Stable, documented, testable pipelines powering ML and product features.
High-quality data consistently available for analytics, modeling, and core product workflows.
Faster iteration cycles for the Engineering and ML teams due to improved tooling.
Clear visibility into data quality and reliability.
Strong cross-functional collaboration and communication.
Build core systems at the heart of a fast-growing AI company.
High autonomy, high impact, zero bureaucracy.
Work with a talented, ambitious team solving meaningful problems.
Shape the data platform from the ground up.
At Artisan, we're creating AI Employees, called Artisans, and software which is beautiful, easy to use, and replaces the endless stack of point solutions.
We're starting with outbound sales. Our platform contains every tool needed for outbound sales - B2B data, AI email sequences, deliverability optimization tools and so much more.
Ava, our AI BDR, operates within our platform. She automates:
- Lead discovery with access to over 300M B2B contacts
- Lead research, with 10s of data sources
- Choosing a sales strategy and writing + sending hyper-personalized emails
- Managing deliverability with a suite of tools - from email warmup to placement tests
We're on a mission to create the final boss of software, with every SaaS product needed for sales and AI employees consolidated together in one exceptional platform.
This is the next Industrial Revolution.
