Senior Analytics EngineerUSC1 IDEXX Laboratories, Inc. • Westbrook, Maine, United States

Jetzt Bewerben

Senior Analytics Engineer

USC1 IDEXX Laboratories, Inc.

Westbrook, Maine, United States

Westbrook, Maine, United States

Jetzt Bewerben

Über

Overview 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. 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. This role builds that foundation, ensuring reliable analysis of instrument performance, customer experience, and AI‑enabled insights across IDEXX’s diagnostic portfolio. Responsibilities 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, embedding 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 the models, including automated data quality monitoring and tools that reduce repetitive analysis and recurring reporting effort across the team. Qualifications Deep experience with dbt or comparable transformation and versioned modeling practices; 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; choose the pattern that fits the problem. Git and version control as an ingrained daily practice. Demonstrated ability to operate autonomously at a senior level: scoping work, setting priorities, and delivering without close oversight. Clear, direct communication style; ability to explain technical trade‑offs to non‑technical stakeholders. Genuine curiosity about AI and LLM tooling applied to data; thinking about how structured data and metadata enable intelligent systems. Mindset to turn messy operational data into reusable analytical products, caring about naming conventions and business definitions. Experience working in environments where the data infrastructure was better than the modeled layer on top of it. Ability to be excited about AI beyond hype, seeing how clean, well‑structured data makes it work. Python for data transformation, scripting, or prototyping. Experience with Airflow or similar orchestration tools. Familiarity with data catalog platforms such as Alation, DataHub, or similar. Experience with warehouse‑native AI features such as semantic models, agent frameworks, or natural language query interfaces. Experience building or maintaining semantic layers that serve BI tools, APIs, or agent‑based systems. Background in enterprise environments with complex, multi‑source data ecosystems. Exposure to veterinary diagnostics, medical devices, or healthcare data is helpful but not required. Benefits Base salary range of $130,000 to $150,000 based on experience. Opportunity for annual cash bonus. Health / Dental / Vision Benefits. Day‑One 5% matching 401(k). Additional benefits including financial support, pet insurance, mental health resources, volunteer paid days off, employee stock program, foundation donation matching, and more. Equal Opportunity IDEXX values a diverse workforce and workplace and strongly encourages women, people of color, LGBTQ+ individuals, people with disabilities, members of ethnic minorities, foreign‑born residents, and veterans to apply. IDEXX is an equal opportunity employer. Applicants will not be discriminated against because of race, color, creed, sex, sexual orientation, gender identity or expression, age, religion, national origin, citizenship status, disability, ancestry, marital status, veteran status, medical condition, or any protected category prohibited by local, state, or federal laws.
#J-18808-Ljbffr

Westbrook, Maine, United States

Sprachkenntnisse

English

Hinweis für Nutzer

Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klick auf „Jetzt Bewerben”, um deine Bewerbung direkt auf deren Website einzureichen.

Jetzt Bewerben