Senior Data Engineer

Job not on LinkedIn

🔥 0 minutes ago

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Daybreak

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2024

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

🔥 Funding within the last year

💰 $15M Series A on 2025-07

Artificial Intelligence • SaaS • B2B

Daybreak is an AI-first supply chain planning company (formerly Noodle. ai) that builds domain-specific prediction and decision systems for enterprise supply chains. Their platform combines a data-centric, model-agnostic prediction engine, a decision system that blends AI outputs with human judgment, and AI assistants to automate routine planning tasks while keeping humans in control. Daybreak focuses on making supply chain predictions accessible to business users without coding or data science expertise, improving decision quality, speed, resource utilization, and reducing waste.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• None specified