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Craft

Supply chain risk analytics and resilience

Senior Data Platform Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USARemote

About the Job

Requirements

  • At least 4 years of experience in data engineering.
  • At least 4 years of experience with Python.
  • Experience developing, maintaining, and ensuring the reliability, scalability, fault tolerance, and observability of data pipelines in a production environment.
  • Fundamental knowledge of extract, transform, load and extract, load, transform; batch and streaming; data warehouses; data lakes; and distributed processing.
  • Strong knowledge of the software development life cycle and solid software engineering practices.
  • Familiarity with an infrastructure-as-code approach.
  • Familiarity with technologies including Python, PySpark, Pandas, SQL, PostgreSQL, Elasticsearch, Airflow, Docker, Databricks, Amazon Web Services, Amazon Simple Storage Service, Amazon Batch, Amazon Athena, Amazon Relational Database Service, Amazon DynamoDB, Amazon Glue, Amazon Elastic Container Service, Amazon Neptune, CircleCI, GitHub, and Terraform.
  • Knowledge of artificial-intelligence-assisted coding and experience with Cursor, Copilot, or Codex.
  • A strong track record of using artificial intelligence integrated development environments such as Cursor to rapidly scaffold components and application programming interfaces, refactor legacy codebases, reduce context switching, accelerate documentation, and experiment and prototype with near-instant feedback.
  • Ability to communicate ideas effectively and solve problems independently.

Responsibilities

  • Build and optimize batch and streaming data pipelines.
  • Extract, analyze, and model rich and diverse structured and unstructured datasets.
  • Design software that is easily testable and maintainable.
  • Support data strategies and the organization's data vision.
  • Track emerging data engineering technologies and trends and incorporate modern tooling and best practices.
  • Work on extensible data processing systems that support adding and scaling pipelines.
  • Apply machine learning techniques such as anomaly detection, clustering, regression classification, and summarization to extract value from datasets.
  • Use artificial-intelligence-powered development tools such as Cursor to accelerate development, refactoring, and code generation.

About the Company

Craft

Supply chain risk analytics and resilience

Craft provides a supply chain resilience platform that helps organizations optimize supplier networks and defend against disruptions. It uses a data fabric and AI analytics to give 360-degree visibility of suppliers, allowing users to assess risk, compare options, and collaborate to adjust plans. Its emphasis on regulatory compliance and ethical governance, combined with data-driven insights and collaboration, sets it apart from competitors. The goal is to help organizations sustain operations by building a resilient supplier ecosystem and reducing the impact of disruptions.

Company size
51-200
Company stage
Series B
Total funding
$42M
Headquarters
San Francisco, CA
Founded
2014

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