Senior Data Engineer

What does your role bring to the table?

The Senior Data Engineer serves as a technical powerhouse within Snooze’s data ecosystem, reporting directly to the Vice President of Data Engineering and Analytics. In this role, you will design, harden, and scale the infrastructure required to power advanced analytics and artificial intelligence applications across our 65+ locations. By prioritizing strategy, growth, and monetization in your architectural decisions, you will transform complex data challenges into actionable business value, empowering cross-functional teams and creating a clear ROI for our data platform.

The Position specifics!

Taking on the role of Senior Data Engineer isn’t just about bacon and pancakes. This role requires deep technical execution combined with an understanding of enterprise value creation. The responsibilities of this position include:

●      Enterprise Data Modeling: Architect and implement scalable, robust data models (e.g., dimensional modeling, star schemas) that serve as the single source of truth for both self-service operational reporting and advanced machine learning and AI applications.

●      Advanced SQL & Query Optimization: Write, review, and continuously optimize highly complex SQL queries within Snowflake to ensure performant, cost-effective data retrieval at enterprise scale.

●      Data Warehouse & Lake Security: Harden and optimize our Snowflake data warehouse and AWS S3 data lake environments, ensuring robust governance, security, and scalability.

●      Semantic Layer Optimization: Utilize dbt to build, manage, and continuously improve our enterprise semantic layer, ensuring data consistency and enabling scalable self-service analytics for Operations and Marketing.

●      AI Workflow Integration: Lead the development and integration of AI applications directly into Snooze's operational and back-office workflows. Demonstrate expertise in prompt engineering and optimization to standardize and improve AI interactions across the organization.

●      Machine Learning Deployment: Architect and deploy production-ready machine learning models within an AWS environment for applications such as optimizing labor forecasting, menu engineering, and supply chain efficiency.

●      API Development: Design, build, and maintain robust, high-performance data APIs using frameworks such as FastAPI or Flask to seamlessly integrate data products into our evolving tech stack.

●      Pipeline Orchestration & Resilience: Develop and maintain complex data pipelines using Apache Airflow. Enforce strict pipeline reliability standards and rigorous error handling, such as ensuring data pipelines explicitly error out and trigger alerts when critical vendor files are missing.

Is this role the right fit for you?

If this is the right role for you, you must possess the following skillsets:

●      Data Architecture & Modeling: Proven ability to design scalable, dimensional data models that translate complex business logic into intuitive, efficient data structures.

●      Advanced SQL: Expert-level SQL proficiency, including advanced query optimization, performance tuning, cost-reduction strategies, and complex window functions.

●      Apache Airflow: Advanced orchestration, custom operator development, and strict error handling implementation.

●      dbt: Hands-on experience structuring, testing, and optimizing a robust semantic layer.

●      Machine Learning: Applied experience deploying production-ready ML models within an AWS ecosystem.

●      FastAPI / Flask: Proven ability to build secure, high-performance API frameworks for data serving.

●      AI Integration: Demonstrated capability to integrate AI/LLMs into enterprise workflows and operational pipelines.

●      An entrepreneurial spirit with a focus on delivering technical solutions that create enterprise value and operational leverage.

●      Decisive problem-solving skills to improve organizational efficiency.

●      A positive, glass-half-full attitude about your work.

●      Ability to have fun, dance, and laugh under/during stressful situations (yes, seriously)

Let’s talk prerequisites! (Education, credentials, and experience)

●      Must be authorized to work in the United States.

●      5+ years of dedicated experience in data engineering, complex data modeling, deploying machine learning models, and scaling cloud data ecosystems.

●      Deep practical expertise in modern cloud data platforms, orchestration tools, and languages (e.g., Snowflake, Airflow, SQL, Python).

Let’s get physical! (additional requirements)

●      Must have the stamina to work 40 to 45 hours per week.

●      Minimal travel required.

●      Home base is in Denver, CO at the Snooze Restaurant Support Center (3 days a week required in office)

The Bennie-fits

This role comes with some sweet perks! See below:

●      Competitive Annual Snooze Incentive Bonus Program

●      Snooze equity program eligibility immediately upon hire or after one year in role

●      Competitive Health, Dental, Vision, Pet and Accident Insurance Plans with employer contribution

●      Employer Paid Short Term Disability and Life insurance benefits

●      401k/Roth 401k Plans

●      Snooze Work Hard, Play Hard Days (Unlimited Time off Program)

●      Five (5) paid sick days within a calendar year (up to 48 hours)

●      Paid Holidays (RSC Holiday Schedule), Birthday and Snooze Anniversary Date

●      Snooze Cell Phone Stipend

●      Snooze Meal Benefits for Yummy Snooze Food

●      Other benefits including field trips, community engagement, and personal and professional growth

The Nitty Gritty Details

Denver area base salary range: $140,000 to $170,000 per year