Data Engineer

Data Engineer

Build the data foundation that powers Auger's Supply Chain OS, AI systems, and execution workflows. Auger is building an operating system for supply chain teams. Our customers rely on Auger to understand reality and change it: reporting, AI-powered decision support, and write-back execution systems that operate at scale. At the core of this system is Data Engineering. This role owns the transformation of messy, customer-shared data into a unified, production-grade ontology that directly powers analytics, AI workflows, and execution systems. This is not a "move data from A to B" role. This is semantic ownership at the heart of the product.

As a Data Engineer, you will leverage new and existing customer data sources ingested into Auger's core data lake and transform them into our ontology. We're seeking teammates who love data of all kinds, are masters of building efficient, scalable, operable data pipelines, and are ready to take hands-on coding ownership in the following areas:

• Own the data lifecycle end-to-end, from ingestion to production-ready ontology
• Ingest data from databases, streams, batch files, and incremental feeds
• Design and operate medallion-style lakehouse pipelines (bronze → silver → gold)
• Transform raw inputs into a consistent digital twin of supply chain reality
• Serve high-quality data to analytics, AI workflows, and write-back systems
• Own data correctness and reliability in production, including monitoring, on-call, and incident response
• Build data quality checks, validations, and safe backfill strategies
• Use AI-assisted tools responsibly, reviewing and hardening generated code
• Reduce complexity by simplifying pipelines and automating repetitive work

What You Bring

• Degree in Computer Science, Mathematics, Statistics, or other data-intensive discipline with substantive engineering experience
• 2+ years demonstrated development experience using SQL, Scala, Spark, Flink, Beam, and/or Python
• 2+ years demonstrated experience in data management (structured and unstructured) and modern database technologies
• Experience building and operating production data pipelines in distributed systems
• Hands-on experience with lakehouse or warehouse architectures
• Strong schema design skills for structured and semi-structured data
• A production mindset—you've owned systems that break and fixed them
• Experience supporting AI/ML or AI-powered products
• Familiarity with streaming or incremental processing
• Experience with data quality, observability, or anomaly detection
• A deep curiosity and eagerness to problem solve without a playbook. If you require intense structure and process, this is not the place for you
• Ability to work collaboratively through ambiguity, with urgency, patience, and good humor