Principal Data Engineer

Description

The company was founded in 2017 and works to improve the health and wellbeing of older Americans. Its care platform combines data and AI with clinical and service experience.

The Data Platform team builds the infrastructure that lets the company use data to deliver better service and care.

You will build tools that help data scientists and engineers ship scalable, reliable data pipelines, machine learning models and LLM-powered tools. The platform runs on Snowflake, Apache Airflow, dbt, Kubernetes and Terraform, and draws on models from the leading AI labs.

Recent work includes a change-data-capture pipeline that streams data into Snowflake, a custom Snowflake SQL formatter, and an internal semantic layer with a data agent that answers plain-language questions and builds dashboards and analyses. Most of the team's tools are written in Go.

The team picks the right tool for each job, weighs performance, reliability and maintainability, regularly revisits its decisions, shares knowledge and works without silos. Coding agents are part of the daily workflow.

Responsibilities

• Design, build and maintain a reliable, scalable data platform for analytics, machine learning and AI workloads.
• Extend the infrastructure under the semantic layer and data agent, including how LLMs find, interpret and safely query company data.
• Set up evaluation, monitoring and quality practices for AI systems built on the platform so accuracy can be measured and regressions caught.
• Work with data science and product engineering to build tools that let them ship dependable data and AI products.
• Keep data available, high quality and reliable across the platform.
• Find weak spots in the platform and suggest improvements.
• Take proposed solutions from design through to delivery.
• Set best practices for data modelling, pipelines and testing.

Requirements

• You are comfortable with ambiguity and want to stay close to business problems.
• You are practical about AI: enthusiastic about what it can do and clear on where it is the wrong tool.
• You are willing to keep learning, especially as the AI field changes quickly.
• You enjoy collaborating and improving as a team, and you can work independently and set your own direction.
• Required: 5+ years working as an individual technical contributor.
• Required: 5+ years of experience with data platforms.
• Required: experience with cloud data warehouses such as Snowflake, BigQuery or Redshift.
• Required: experience developing in Python or Go.
• Required: experience with a workflow orchestrator such as Airflow, Luigi, Dagster or Prefect.
• Required: a strong grasp of data warehousing and data modelling principles.
• Required: experience with semantic or metrics layers such as dbt Semantic Layer, Cube or LookML.
• Required: ability to work in a startup environment that moves quickly.
• Desired: regular use of coding agents such as Claude Code, Codex or Cursor.
• Desired: hands-on experience building or supporting applications that use LLMs through Anthropic, OpenAI or similar APIs.
• Desired: experience designing evaluations for LLM systems, such as text-to-SQL accuracy.

Conditions

The posted pay range is what the company reasonably and in good faith expects to pay for this role at the time of posting.

After interviews begin, a talent partner will share more about compensation and the total rewards package.

The base salary offered depends on the applicant's qualifications, years of relevant experience, specialised skills, education, certifications or licences, and the location where they live or will work.

Total rewards apply to full-time employees only. Interns and contractors are not eligible.

The company is an equal opportunity employer and does not discriminate on any basis protected by law.

Benefits

• Health, dental and vision plan with low or no premium for employees.
• Generous paid time off.
• $100 monthly mobile or internet stipend.
• Stock options for all employees.
• Bonus eligibility for all roles except Director and above; commission eligibility for Sales roles.
• Parental leave program.
• 401K program.
• And more.