Senior Data Engineer

About the opportunity

Daybreak AI is building next-generation supply chain intelligence for the world's most complex manufacturing and logistics operations. Our Data Engineers are the backbone of that mission, designing, building, and operating the data infrastructure that powers our AI products.

What you'll do

• Design, build, and maintain production-grade data pipelines handling large-scale supply chain datasets
• Own end-to-end data modeling, warehousing architecture, and pipeline reliability across multiple customer environments
• Collaborate with Data Science, DevOps, Infrastructure, and Customer Success teams to deliver and iterate on product deployments
• Debug complex pipeline failures and performance bottlenecks across distributed systems
• Drive improvements to engineering practices, tooling, and deployment automation
• Mentor and support junior data engineers, fostering technical growth within the team
• Contribute to Daybreak's culture of continuous learning and operational excellence

Must have

• 5+ years of experience in data engineering, with demonstrated ownership of production pipelines
• Strong proficiency in Python for data engineering workloads
• Advanced SQL skills across multiple databases (PostgreSQL and others)
• Hands-on experience with pipeline orchestration tools such as Apache Airflow or Dagster
• Experience working with distributed data systems Spark, Hive, or HDFS
• Solid understanding of containers and Docker in a development/deployment context
• Strong debugging skills and systematic approach to resolving data quality issues
• Bachelor's or advanced degree in Computer Science, Engineering, or a related field
• Ability to thrive in a fast-paced, evolving environment and pick up new technologies quickly

Helpful to have

• Cloud experience, preferably AWS (S3, EMR, or equivalent services)
• Experience processing large-scale time series data
• Familiarity with Kubernetes for containerized workloads
• Understanding of ML model lifecycle and MLOps pipelines
• Experience working in interdisciplinary teams across engineering and data science