Senior Data Engineer, Craft.co

• 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
• Knowledge of and experience with Amazon Web Services (AWS) and Databricks
• Familiar with infrastructure-as-code approach
• Shows curiosity through asking questions, digging into new technologies, and always trying to grow
• Kind and empathetic with your teammates and others
• Strong problem solving and the ability to communicate ideas effectively
• Self-starter, independent, likes to take initiative
• Familiarity with at least some technologies in our current tech stack:
• Python, PySpark, Pandas, SQL (PostgreSQL), Airflow, Docker
• Databricks & AWS (S3, Batch, Athena, RDS, DynamoDB, Glue, ECS)
• CircleCI, GitHub, Terraform

• We're looking for innovative and driven people passionate about building the future of Enterprise Intelligence to join our growing team!
• Craft is looking for an experienced and motivated Senior Data Engineer to join our DISCoE team (aka our data platform team), which is the team responsible for defining and implementing standards for data storage in Databricks using a medallion architecture, defining patterns for interacting with our data, using automation methods to track and monitor all data, and creating tools for data operations. All to power our supplier risk management products and services
• The DISCoE team is growing and covering areas of the business that in the past were afterthoughts. DISCoE’s mission is to make our data a first class citizen of the business from sourcing and ingestion to structure and consumption
• Building and optimizing data pipelines (batch and streaming)
• Extracting, analyzing and modeling of rich and diverse datasets
• Designing 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
• Applying machine learning techniques such as anomaly detection, clustering, regression classification, summarization to extract value from our data sets

• Unlimited PTO
• Parental Leave
• 99% Benefits Coverage
• 401k plan
• Hybrid Hub Strategy
• Flexible Work Hours

Total funding: $42m

Maintaining a seamless supply chain is essential to the success of most businesses, with procurement teams being responsible for sourcing new suppliers, analyzing inventory data, and generating forecasts. However, analyzing such data requires the repetitive and specialist work of data engineers for both parties, making the sourcing process time-consuming.