Principal Data Engineer

Idexx•Westbrook, ID

1d•Hybrid

About The Position

As a Principal Data Engineer, you will build and maintain the data pipelines that power AI model training and algorithm development for IDEXX inVue Dx and other AI-powered diagnostic products. This is a hybrid role based out of IDEXX's Westbrook, Maine location, with a minimum expectation of two days onsite each week. The Data & AI Center of Excellence (AI Enablement & Model Operations) manages the data foundation behind IDEXX's AI-powered diagnostics. You will join the Data Engineering team, working hands-on in Databricks, dbt, and Snowflake, and serve as a technical anchor for other engineers. This is a senior, hands-on role with ownership of significant pipeline work from start to finish, and an opportunity to set standards for code quality and data modeling across the team. The pipelines you build feed AI models behind IDEXX inVue Dx and other AI-powered diagnostic products, helping veterinary teams care for pets.

Requirements

At least 7 years of experience in data engineering or a closely related field, including production experience.
Strong SQL and Python skills and hands-on experience with dbt.
Experience with a modern cloud data platform; Databricks and/or Snowflake experience is strongly preferred.
Comfort with CI/CD, version control using GitHub, and automated testing for data pipelines.
Experience mentoring or reviewing the work of junior and mid-level engineers.
Experience working directly with Data Science, MLE, or other technical partners to understand their data needs.
Good judgment about when to escalate, make a decision independently, or ask for help.

Nice To Haves

Experience in healthcare, life sciences, or another regulated data environment.
Experience with AI/ML training pipelines or working closely with Data Science or MLE teams.
Familiarity with medallion architecture, SCD2 patterns, or similar data modeling conventions.
A track record of proposing and driving improvements to engineering practices or tooling.

Responsibilities

Design, build, and maintain fault-tolerant production data pipelines in Databricks and dbt Core, following the team's existing medallion architecture and SCD2 patterns.
Own delivery of a portion of the team's roadmap and partner directly with Data Science and MLE colleagues to understand their data needs.
Write and review code, tests, and documentation to a standard other engineers can build on.
Troubleshoot pipeline failures and data quality issues, and build monitoring and alerting to catch problems early.
Contribute to Snowflake integration work, including federated connections and history tracking for source systems.
Mentor junior and mid-level data engineers on code quality, data modeling, and platform best practices.
Review pull requests and pair with teammates on difficult problems.
Help scope and triage incoming Jira tickets, and flag when issues need escalation.
Participate in interviews for future team hires.
Partner with the manager on team standards for testing, deployment, and documentation.