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.

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.
Strong knowledge of SDLC and solid software engineering practices.
Familiar with infrastructure-as-code approach.
Demonstrated curiosity through asking questions, digging into new technologies, and always trying to grow.
Strong problem solving and the ability to communicate ideas effectively.
Self-starter, independent, likes to take initiative.
Familiarity with at least some of the technologies in our current tech stack: Python, PySpark, Pandas, SQL (PostgreSQL), ElasticSearch, Airflow, Docker
Databricks, AWS (S3, Batch, Athena, RDS, DynamoDB, Glue, ECS, Amazon Neptune)
CircleCI, GitHub, Terraform
Knowledge surrounding AI-assisted coding and experience with Cursor, Co-Pilot, or Codex

Senior Data Platform Engineer

Key skills