Principal Data Engineer

🕒 October 15

🦞 Maine – Remote

🦞 Maine – Remote

💵 $140k - $160k / year

⏰ Full Time

🔴 Lead

🚰 Data Engineer

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IDEXX

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1983

🏥 Healthcare

🔬 Science

🤝 B2B

💰 Seed on 1984-02

Healthcare • Science • B2B

IDEXX is a global veterinary diagnostics and services company that develops products and services to improve the health and well‑being of pets, livestock, and to protect public essentials such as clean drinking water. It provides diagnostic tests, laboratory services, point‑of‑care analyzers, and consultation/testing support for scientists, and also offers practice management and clinical software used by veterinary clinics and reference laboratories. IDEXX primarily serves professional and institutional customers (veterinary practices, labs, and agricultural/food/water safety users) with integrated products and services.

📋 Description

• Own and lead the technical strategy and architecture for the DI&T analytics data platform and semantic layer • Design and develop scalable data models and curated datasets • Define and lead the analytics semantic layer, including business logic, metrics, dimensions, relationships, and definitions • Lead reliable production data pipelines and transformation processes • Integrate data from operational systems, warehouses, integration hubs, data lakes, and enterprise sources • Translate business and analytical requirements into scalable, reusable data solutions • Solve complex cross-system data problems and develop innovative solutions • Establish and apply data modeling, engineering, and governance standards • Implement validation, testing, monitoring, and error handling to ensure data quality and reliability • Provide technical leadership and mentorship to analysts, engineers, and technical team members • Serve as subject matter expert for data modeling, dbt, Snowflake, SQL, and analytics engineering • Monitor pipeline and model performance and implement sustainable improvements • Partner with technology and engineering teams to evolve data architecture • Identify opportunities to centralize data, automate workflows, improve integration, and strengthen the data foundation • Set technical priorities aligned with business objectives • Communicate technical concepts, risks, trade-offs, and recommendations to technical and non-technical audiences

🎯 Requirements

• Bachelor’s degree in computer science, data engineering, information systems, or a related field; equivalent combination of education and significant relevant experience will be considered • 7+ years in data engineering, analytics, data architecture, or a related technical discipline • Technical leadership of production data platforms or enterprise-scale analytics environments • Deep dbt or equivalent experience • Deep Snowflake or equivalent analytical platform experience • Advanced experience with dimensional, wide-table, and hybrid modeling approaches • Expert SQL capabilities • Production data engineering experience, including pipelines, orchestration, monitoring, error handling, and operational support • Strong Git and CI/CD experience • Python or other scripting language experience preferred • Experience applying AI-assisted development tools preferred • Ability to evaluate technical trade-offs and make architecture decisions • Ability to influence architecture and system design across organizational boundaries • Ability to translate complex technical concepts for technical and non-technical stakeholders • Strong understanding of data governance, data lineage, business definitions, naming conventions, metadata, and context engineering • Ability to work independently and determine priorities with limited direction • Strong problem-solving skills for complex, ambiguous, and novel technical problems • Cloud certifications and data engineering certifications preferred, not required

🏖️ Benefits

• Opportunity for annual cash bonus • Health / Dental / Vision Benefits Day-One • 5% matching 401k • Financial support • Pet insurance • Mental health resources • Volunteer paid days off • Employee stock program • Foundation donation matching • Competitive compensation and incentives • Positive and respectful work culture • Learning and discovery opportunities

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