AI Enablement Software Engineer - Data Pipelines

Auger Inc.; Bellevue, Northern (WA, KY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Auger Inc. is seeking a Software Development Engineer with a strong data engineering background to own end-to-end pipelines and data transformations for production-grade systems, including robust testing and quality gates.

You will collaborate with product, science, and platform teammates, apply validation-first data practices, and improve reliability through tests, monitoring, and robust operational habits.

Qualifications

• 4+ years of professional development with SQL and Python in production; Spark or equivalent large-scale batch processing preferred
• 3+ years in data work (structured and semi-structured) with modern warehouses/lakehouses and practical schema design
• Ownership mindset: debug, improve reliability, and tie work to customer outcomes
• Validation-first data habits with checks, regression protection, and agent-native verification
• Clear communication and collaboration; contribute to codebase improvements
• Nice to have: experience in supply chain, planning, or fulfillment domains

Responsibilities

• Deliver end-to-end on pipelines and transformations with production-grade logic and validation.
• Operate in an agent-native style, leveraging AI tools for data exploration, transformation, and troubleshooting.
• Build and maintain integration points between data pipelines and ML pipelines with schema-bound datasets.
• Monitor, alert, and participate in incident remediation; expand automated checks and regression coverage.
• Collaborate with product, science, and platform teams to clarify requirements and deliver reliable work.

Skills

SQL

Python

Spark

Scala

Flink

Beam

Data pipelines

ETL

Schema design

Production debugging

Education

CS/Math/Stats degree

Tools

Jupyter notebooks

Job description

Auger Inc. is seeking a Software Development Engineer with a strong data engineering background to own end-to-end pipelines and data transformations for production-grade systems, including robust testing and quality gates.

You will collaborate with product, science, and platform teammates, apply validation-first data practices, and improve reliability through tests, monitoring, and robust operational habits.