Data Engineer

ABOUT VEG

In 2014, VEG was born with a mission to help people and their pets when they need it most by challenging norms and fixing the ER experience. Since then, we’ve expanded rapidly, with hospitals nationwide open 24/7/365, and created an ER experience that focuses on what our pets and pet parents really need. We’ve done the same for our people (VEGgies), finding a way to say YES so they are empowered to achieve great things, grow in unexpected ways, and find a place where they truly belong.

We’re rethinking emergency care from every angle—from how we run our hospitals to how we support the people working inside them. That’s where our headquarters team comes in. Whether building technology to make our hospitals more efficient, recruiting and growing incredible VEGgies, or bringing our brand to life through marketing, our VQ (VEG Headquarters) team makes it all possible—ensuring our hospitals and people have everything they need to help pets and their families.

VEG is a 2025 and 2026 certified Great Place to Work®.

 

THE JOB

At VEG, we find a way to say YES — so you can build the data foundation that powers how the world's veterinary emergency company runs. As a Data Engineer on our Data Platform and Infrastructure team, you'll deliver trusted, scalable data products across our clinical, operational, and people data — the data behind every report, analysis, and AI use case at VEG. This is a deeply Snowflake-centric role: Snowflake is the core of our platform, and your day-to-day lives in Snowflake-native features, dbt transformation, and a fast-growing suite of AI/LLM capabilities. We're expanding our AI capabilities quickly, and you'll champion AI-assisted development as a core part of how you work. If you're as comfortable writing advanced SQL as you are thinking through architecture and partnering across teams, you'll grow here in ways you didn't expect. This role is hybrid, with presence at our White Plains, NY office 2–4 times per week.

WHAT YOU’LL DO

• Build and maintain the pipelines. Develop and maintain ELT pipelines that onboard new clinical, operational, and people data into VEG's Snowflake warehouse and dbt Data Vault, partnering with engineering and business stakeholders on requirements, reliability, and performance.
• Own Snowflake as the platform. Use Snowflake-native capabilities — Snowpipe, Openflow, Tasks, Cortex, Streamlit — to design scalable, performant solutions, applying best practices for query optimization, clustering, and resource management as our analytical workload grows.
• Model trusted, analysis-ready data. Curate clean datasets from raw data and write business logic in dbt so reporting, analytics, and AI use cases run on data people can rely on.
• Protect data quality. Monitor pipeline health, run detailed QA, and resolve data quality issues across every integrated source.
• Champion AI-assisted development. Use agentic coding tools (Claude Code, GitHub Copilot) as a standard part of your workflow, and build LLM-integrated pipelines including transcription summarization, automated tagging, and Cortex-powered workflows.
• Partner on what's next. Design data structures that support AI/ML use cases — feature engineering, embeddings, prompt-ready datasets — provide thought partnership on analytics, and contribute documentation that enables self-service across VEG.

 

WHAT YOU NEED

• 5+ years of data engineering experience building and maintaining production ELT pipelines (Bachelor's in Computer Science or equivalent experience)
• Deep, hands-on Snowflake expertise — this is the platform, not one tool among many; experience with Snowpipe, Openflow, Tasks, Cortex, and Streamlit strongly preferred
• Strong dbt and Data Vault proficiency, expert-level SQL using Snowflake-native functions, and Python proficiency (Fivetran for ELT a significant plus)
• Fluency with Git and GitHub on a collaborative engineering team — branching workflows, pull requests, and code review
• Regular use of AI-assisted development, plus familiarity with LLM-integrated data pipelines such as tagging, summarization, and embeddings
• Detail-oriented with high accuracy, strong intellectual curiosity, and a collaborative, working style

 

WHO YOU ARE

• Empathetic, instinctively taking a people-centric approach, whether supporting your colleagues or making an effort to understand different perspectives
• Have a sense of humility; acknowledging mistakes, sharing credit with others, and lifting up your team’s’ accomplishments
• Feel a strong sense of ownership over your work, taking responsibility for outcomes and staying co