Sr. Data Engineer

Auger Inc.; Bellevue, Northern (WA, KY); Hybrid; USD 140,000 - 200,000; Full time

Job summary

Auger Inc. is building an operating system for supply chain teams and seeks a Senior Data Engineer to own the semantic evolution of data into a unified ontology powering analytics and AI workflows.

You will ingest diverse data sources, design lakehouse pipelines, and ensure data correctness in production while partnering with product and platform teams to deliver durable technical solutions.

Qualifications

• Degree in Computer Science, Mathematics, Statistics, or other data-intensive discipline with substantive engineering experience.
• 5+ years demonstrated development experience using technologies like Python, SQL, Scala, Spark, Flink, and Beam.
• 5+ years demonstrated experience in data management (structured and unstructured) and modern database technologies.
• Proven experience owning and evolving large-scale production data systems in distributed environments.
• Hands-on experience designing and operating lakehouse or warehouse architectures at scale.
• Strong schema design skills and deep intuition for data modeling in complex domains.
• A production mindset—you’ve owned critical systems, led incident resolution, and driven long-term fixes.
• Experience supporting AI/ML or AI-powered products where data quality directly impacts outcomes.
• Familiarity with streaming or incremental processing at scale.
• Experience defining data quality, observability, anomaly detection, or reliability standards.
• A deep curiosity and eagerness to problem solve in ambiguous, high-impact problem spaces without a playbook.
• Ability to lead through ambiguity with urgency, patience, and good judgment while raising the bar for others.
• Strong communication and collaboration skills.
• A plus if you have prior experience in the supply chain domain.

Responsibilities

• Own and evolve the data lifecycle across systems, from ingestion through production-ready ontology.
• Ingest data from databases, data streams, batch files, and incremental feeds.
• Define standards for and operate medallion-style lakehouse pipelines (bronze → silver → gold).
• Transform raw inputs into a consistent digital twin of supply chain reality that scales across customers.
• Serve high-quality data to analytics, AI workflows, and write-back systems with clear correctness guarantees.
• Own data correctness and reliability in production, including monitoring, on‑call, incident response, and post‑incident systemic improvements.
• Define and enforce data quality checks, validations, and robust backfill strategies.
• Use AI‑assisted tools responsibly, setting expectations for review, validation, and production readiness of generated code.
• Reduce complexity at scale by simplifying pipelines, eliminating redundancy, and automating recurring workflows.
• Partner with product, science, and platform tooling teams to translate ambiguous needs into durable technical designs.

Skills

Python

SQL

Scala

Spark

Flink

Beam

Data modeling

Lakehouse

Production data systems

Data quality

Observability

Streaming processing

Communication

Leadership

Education

Bachelor’s degree in CS, Math, Stats or related data-intensive field

Job description

About the Role

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 sets direction for and owns the evolution of 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 system-level semantic ownership at the heart of the product.

What You’ll Do

As a Senior 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 and durable data systems, and are ready to take hands‑on ownership beyond individual pipelines in the following areas:

• Own and evolve the data lifecycle across systems, from ingestion through production-ready ontology
• Ingest data from databases, data streams, batch files, and incremental feeds
• Define standards for and operate medallion-style lakehouse pipelines (bronze → silver → gold)
• Transform raw inputs into a consistent digital twin of supply chain reality that scales across customers
• Serve high-quality data to analytics, AI workflows, and write-back systems with clear correctness guarantees
• Own data correctness and reliability in production, including monitoring, on‑call, incident response, and post‑incident systemic improvements
• Define and enforce data quality checks, validations, and robust backfill strategies
• Use AI‑assisted tools responsibly, setting expectations for review, validation, and production readiness of generated code
• Reduce complexity at scale by simplifying pipelines, eliminating redundancy, and automating recurring workflows
• Partner with product, science, and platform tooling teams to translate ambiguous needs into durable technical designs

What You Bring

• Degree in Computer Science, Mathematics, Statistics, or other data-intensive discipline with substantive engineering experience
• 5+ years demonstrated development experience using technologies like Python, SQL, Scala, Spark, Flink, and Beam
• 5+ years demonstrated experience in data management (structured and unstructured) and modern database technologies
• Proven experience owning and evolving large-scale production data systems in distributed environments
• Hands‑on experience designing and operating lakehouse or warehouse architectures at scale
• Strong schema design skills and deep intuition for data modeling in complex domains
• A production mindset—you’ve owned critical systems, led incident resolution, and driven long-term fixes
• Experience supporting AI/ML or AI‑powered products where data quality directly impacts outcomes
• Familiarity with streaming or incremental processing at scale
• Experience defining data quality, observability, anomaly detection, or reliability standards
• A deep curiosity and eagerness to problem solve in ambiguous, high‑impact problem spaces without a playbook
• Ability to lead through ambiguity with urgency, patience, and good judgment while raising the bar for others
• Strong communication and collaboration skills
• A plus if you have prior experience in the supply chain domain