Sr. Data Platform Engineer (US)

About the role

ABOUT CRAFT:

Craft is the leader in supplier risk intelligence, enabling enterprises to discover, evaluate, and continuously monitor their suppliers at scale. Our AI research and monitoring agents deliver real, actionable intelligence, by operating on top of our unique, proprietary data platform - this helps our customers make better, more informed decisions for their business, faster and strategically secure critical supply chains from risk. Our customers include Fortune 500 companies, government agencies, and global service platforms. We’ve developed distribution partnerships with some of the largest integrators and software platforms globally.

We are a post-Series B high-growth technology company backed by top-tier investors in Silicon Valley and Europe, headquartered in San Francisco with hubs in Seattle and Warsaw. We support remote and hybrid work, with team members across North America and Europe.

We are looking for innovative and driven people passionate about building the future of Enterprise Intelligence to join our growing team!

ABOUT THE ROLE:

We’re growing quickly and looking to hire several senior-level data engineers for multiple teams. Each team is responsible for a key product within the organization. As a core member of the team, you will have great say in how solutions are engineered and delivered. Craft gives engineers a lot of responsibility and authority, which is matched by our investment in their growth and development.

Our data engineers carry a lot of software engineering responsibilities, so we're looking for engineers who have strong Python coding experience, Pandas expertise, and solid software engineering practices.

WHAT YOU’LL DO:

- Build and optimize data pipelines (batch and streaming).

- Extracting, analyzing and modeling rich and diverse datasets of structured and unstructured data.

- Design software that is easily testable and maintainable.

- Support in setting data strategies and our vision.

- Keep track of emerging technologies and trends in the Data Engineering world, incorporating modern tooling and best practices at Craft.

- Work on extendable data processing systems that allows to add and scale pipelines.

- Apply machine learning techniques such as anomaly detection, clustering, regression classification, and summarization to extract value from our data sets.

- Leverage AI-powered development tools (e.g. Cursor) to accelerate development, refactoring, and code generation.

WHO YOU ARE:

- 4+ years of experience in Data Engineering.

- 4+ years of experience with Python.

- Experience in developing, maintaining, and ensuring the reliability, scalability, fault tolerance, and observability of data pipelines in a production environment.

- Have fundamental knowledge of data engineering techniques: ETL/ELT, batch and streaming, DWH, Data Lakes, distributed processing.