Principal Software Development Engineer

Auger Inc.; Bellevue, Northern (WA, KY); Hybrid; USD 190,000 - 250,000; Full time

Job summary

Auger Inc. in Bellevue, WA seeks a Principal Software Development Engineer to lead hands-on data engineering and elevate the design and operation of critical data systems.

You will design AI-native frameworks, define lakehouse architectures, and ensure durable data models aligned with product, science, and user needs. Join a team building AI-enabled capabilities with measurable outcomes.

Qualifications

• 10+ years in professional development with 8+ years hands-on SQL and Python
• Experience owning large-scale production data systems in distributed environments
• Strong data modeling, schema design, and data quality practices
• AI-native workflow experience with rigorous validation of pipelines and SQL
• Leadership and communication across technical and non-technical partners

Responsibilities

• Design and implement reusable, agentic AI frameworks across heterogeneous data sources; generate ETL logic and schema contracts
• Own data engineering architectural designs for lakehouse pipelines and data quality standards
• Partner with product, science, and data-tools platform to align data models and contracts with customer experience
• Define operating excellence: tests, observability, SLOs, incident response, and backfill/replay strategies
• Bridge data pipelines and ML: turn outputs into schema-bound datasets and reliable writes to semantic layer

Skills

SQL

Python

Spark

Data management

Data quality

Observability

Education

Bachelor's degree in Computer Science or related field

Job description

About the Team

Every autonomous execution decision Auger makes starts with the AI Enablement Engineering team. This team transforms complex, disconnected customer data into a rich semantic backbone that gives our AI systems a deep understanding of each customer's business. This team's work gives our AI the context it needs to reason, plan, and execute. This isn't just a data engineering team. It's the team building the tools and the layer that gives Auger a competitive edge and enables delivery of measurable business outcomes for our customers.

What You'll Do

As a Principal Software Development Engineer, you bring a strong data engineering background. You will lead hands-on execution while raising the bar for how we build, validate, and operate data systems.

• Design and implement reusable, agentic AI frameworks across heterogeneous customer data sources so the team can rapidly discover schemas and semantics, generate ETL transformation logic in medallion style that hydrates the gold semantic layer, write performant SQL, and run efficient end-to-end data troubleshooting in a consistent, scalable way. Mentor the team on AI-native best practices.
• Own data engineering architectural designs and shape technical direction for the data team: standards for medallion-style lakehouse pipelines, boundaries between layers, evolution strategies, and data quality standards.
• Partner across product, science, and the data-tools platform to translate ambiguous needs into durable designs - aligning data models, semantics, and schema contracts with what customers experience in the product. Align business validation rules and data contracts with the Science team, and requirement-definition contracts with the Product team.
• Operating excellence: Practice operating excellence and test-driven engineering for data: define what "correct" means for critical datasets, and encode that in dev → test → prod paths. Institutionalize observability and reliability engineering for data: SLOs, monitoring, incident response, backfill/replay strategy, and elimination of recurring failure modes.
• Own the interface where data pipelines and ML pipelines meet. Turn data pipeline outputs into schema-bound datasets that feed machine learning. Turn ML results into reliable writes to the semantic layer. Define and enforce clear schemas and contracts to decouple fast-moving model logic from the system of record.

What You Bring

• Degree in Computer Science or another data-intensive field, with principal-level experience. 10+ years in professional development, including 8+ years hands-on with SQL and Python and strong familiarity with at least one large-scale engine (e.g. Spark). 8+ years across data management (structured and semi-structured), modern warehouses/lakehouses, ETL/validation, and schema design in complex domains.
• Production ownership: Track record owning large-scale production data systems in distributed environments-on-call, incidents, and lasting reliability improvements (not just one-off fixes).
• Engineering discipline for data: Test-driven habits for transforms - unit/integration patterns, contract tests between layers, and data quality checks tied to business meaning. Experience defining standards for quality, observability, anomaly detection, or reliability and getting teams to adopt them.
• AI-native workflow: Comfortable with AI-assisted development for data work, with rigorous validation—you recognize when generated SQL or pipelines are wrong and know how to prove they're right.
• Leadership & Communication: Technical leadership through ambiguity - set direction for frameworks and conventions, mentor others, communicate clearly both with customers and with internal technical and non-technical partners.
• Deep curiosity in ambiguous, high-impact problems; sound judgment under urgency; patience to fix root causes, not symptoms.
• A plus if you have prior experience in supply chain, planning, or fulfillment domains.