Staff Data Engineer

Artisan

$120K — $160K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years of experience in Data Engineering, ML Engineering, Backend Engineering, or similar roles.
  • Proficiency in Python, SQL, and modern data tools like dbt, Airflow, or Dagster.
  • Experience designing ETL/ELT pipelines for production environments.
  • Familiarity with cloud platforms such as AWS, GCP, or Azure.
  • Understanding of data lakes, warehouses, and vector databases.
  • Experience with API integration and semi-structured data formats (e.g., JSON).
  • Strong data modeling and optimization skills, with bonus points for experience related to LLMs or ML training pipelines.

Responsibilities

  • Design, build, and maintain scalable data pipelines for large data volumes.
  • Manage data ingestion from both third-party APIs and internal systems.
  • Develop data models and schemas optimized for machine learning applications.
  • Collaborate with ML engineers to prepare datasets for model training and evaluation.
  • Implement monitoring and validation processes for data quality.
  • Support product engineers with complex data flow requirements for new features.
  • Contribute to architecture decisions and best practices for data governance.

Benefits

  • High autonomy with the opportunity to impact core system design.
  • Work within a talented and ambitious team that addresses significant challenges.
  • Be part of a fast-growing AI company, shaping the data platform from inception.
Full Job Description
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
  1. Introductory chat with our recruiter
  2. 1 hour technical interview with an engineer
  3. 1 hour technical interview with an engineer
  4. 30-minute interview with Sam, our CPTO
  5. 15-minute culture and values interview with Jaspar, our CEO


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