About The Role: 

Paytient is looking for an Analytics Engineer to partner closely with engineering, product, and marketing stakeholders to deliver data products that drive operational efficiency and product improvement. You’ll enable us to get 1% better each day and further our mission of helping millions of Americans access and afford healthcare. This is an exciting opportunity to get in on the ground floor of our analytics operations. As a member of a small but growing team, you’ll have an opportunity to make a large impact, shaping the future of Paytient. Our ideal candidate has prior experience as an early member of a venture-backed startup’s analytics and data team.

Our “remote with roots” model allows us to work where we thrive and gather as needed, often in our home office in Columbia, Missouri. This role can be performed from anywhere in the continental U.S., with the exception of Montana.

What You'll Do: 

• Full stack analytics engineering - you’ll use dbt, Python, and SQL to transform raw data from our application databases and product/marketing/CX tools like Iterable, Heap, and Intercom into actionable datasets for cross-functional teams
• Maintain our data governance and quality standards by creating data tests in dbt and publishing data dictionaries and documentation that non-technical stakeholders can understand
• Utilize Looker and LookML to create well-documented explores that can be self-serviced by users across the company
• Surface actionable insights through high-quality dashboards and reports
• Drive additional value from datasets using Machine Learning and Generative AI

What You'll Bring: 

• 2 years of experience as an Analytics Engineer, Data Engineer, or BI Engineer
• Expertise in Python, dbt, and SQL - we use BigQuery as our data warehouse
• Familiarity with Looker
• Experience consuming data from any of the following platforms: Heap, Amplitude, Iterable, Hubspot, Stripe, Iterate, Trustpilot
• Knowledge of the analytics engineering development process (modeling, change management, and other best practices)
• Strong written and verbal communication skills to effectively relate data to coworkers
• Excellent critical thinking skills to help solve business problems and make decisions