Senior Analytics Engineer

We are seeking a Senior Analytics Engineer to build the trusted data foundation behind Point-of-Care analytics, reporting, and emerging AI-enabled insight generation. You'll own the transformation and semantic layer that sits between raw data infrastructure and the analysts, applications, and AI tools that consume it.

Why this role matters:

Point‑of‑care diagnostics generate some of the most valuable data in IDEXX, but that data is only as powerful as the models, definitions, and structure behind it. Today, analysts, applications, and emerging AI tools all depend on a trusted, well‑modeled layer to deliver accurate insights. This role builds that foundation. Your work determines how reliably our teams can analyze instrument performance, understand customer experience, and generate AI‑enabled insights across IDEXX’s diagnostic portfolio. When the modeled layer is clean, tested, documented, and consistent, everything built on top of it becomes faster, more accurate, and more scalable.

In this Role You will:

• You'll design and maintain modeled datasets in Snowflake that support product analytics, customer experience insights, and operational reporting across IDEXX's diagnostic instrument portfolio.

• Own the transformation layer in Snowflake, building and maintaining modeled datasets (silver/gold tier) from raw and bronze-tier sources. Design for clarity, performance, and reuse.

• Build and maintain a semantic layer that makes our data discoverable and consumable by analysts, AI agents, and data catalog platforms. Embed business definitions, metric logic, and relationship metadata into the models and their documentation.

• Define, document, and help drive adoption of data modeling standards, testing practices, and documentation norms across the team's Snowflake environment. Establish patterns that analysts and engineers can follow consistently.

• Partner with our Senior Data Engineer on medallion architecture decisions, taking ownership of the transformation logic so infrastructure work can stay focused on orchestration, ingestion, and platform reliability.

• Support and extend our data catalog (Alation) by maintaining asset documentation, lineage, and discoverability. Make self-service real, not aspirational.

• Serve as a technical resource and mentor across the analytics pillar, raising the floor on SQL rigor, version control practices, and data modeling fluency.

• Engage directly with business stakeholders and cross-functional partners to understand data needs, translate them into scalable model designs, and challenge requirements when the better answer is to reshape the question.

• Help design and deploy AI-enabled workflows and agent applications against it, including automated data quality monitoring and tools that reduce repetitive analysis and recurring reporting effort across the team.

What you need to succeed:

• Deep experience with dbt or comparable transformation and versioned modeling practices. You should have strong convictions about project structure, testing strategy, and documentation standards.

• Advanced Snowflake proficiency, including performance tuning, architecture understanding, and the ability to design models that scale.

• Strong data modeling skills spanning dimensional, wide-table, and hybrid approaches.

• You choose the pattern that fits the problem, not the one you're most comfortable with.

• Git and version control as an ingrained daily practice, not an afterthought.

• Demonstrated ability to operate autonomously at a senior level: scoping work, setting
  priorities, and delivering with