Senior Analytics Engineer

Who We Are
Founded in 2013, Thistle is a food-tech startup empowering our customers to get and stay healthy while improving the sustainability of our food system. We make delicious, ready-to-eat plant-forward meals, snacks, and juices delivered right to our customers' doorsteps. Our convenient subscription service empowers customers to improve their personal and planetary health by incorporating more plants into their diet.

About The Role
The Senior Analytics Engineer will play a critical leadership role in shaping and scaling Thistle's data infrastructure, strategy, and culture. You will be responsible for driving the evolution of our modern data stack, delivering robust and high-quality data models, and enabling strategic, data-informed decisions throughout the business.

As a senior member of the Analytics team, you'll act as both a technical expert and thought partner to cross-functional leaders, including marketing, product, engineering, operations, and finance. Your work will have a direct impact on Thistle's growth trajectory, operational efficiency, and customer experience.

How You'll Make a Difference

• Own the architecture and governance of Thistle's end-to-end data infrastructure, ensuring scalability, reliability, and adherence to best practices.
• Lead the design and implementation of our core data models and pipelines (ETL/ELT), enabling advanced analytics, reporting, and experimentation.
• Drive cross-functional alignment on data definitions, metrics, and source-of-truth models to ensure consistency and clarity across teams.
• Develop and mentor analytics engineers and analysts, elevating technical standards and fostering a data-driven mindset throughout the company.
• Serve as a strategic partner to senior leadership by identifying opportunities for data to unlock business value and advising on high-impact initiatives.
• Continuously optimize the performance of our data warehouse (e.g., Snowflake, BigQuery, or Redshift), workflows, and query efficiency.
• Champion best-in-class tooling and practices, including dbt, Airflow, version control, testing frameworks, and documentation standards.
• Support self-serve analytics by building scalable, intuitive data products, dashboards, and exploration tools tailored to business stakeholders.