Associate Analytics Engineer

About Analytics Engineering at CircleCI

The Analytics Engineering team at CircleCI applies software engineering rigor to our data systems. We design the architecture, governance, and tooling that allows teams across the company to access and act on high-quality data. We define what data means, govern how it's used, and deliver it to the people, systems, and AI agents that depend on it. We're looking for someone who brings technical curiosity, attention to detail, and an entrepreneurial mindset and who wants to grow into a full-stack analytics engineer over time.

As an Associate Analytics Engineer at CircleCI, you will work alongside our Analytics Engineering team to help bridge the gap between our data platform engineers and the rest of the business. You'll contribute to delivering well-defined, transformed, tested, and documented data to business users and downstream systems, helping the company strategically use data to operate and grow.

Must be currently located in EST Timezone (Open to Remote, US EST OR Remote, Ontario, Canada.

What you'll do:

• Build and maintain data models and pipelines that deliver well-defined, tested, and documented data to business users and downstream systems
• Contribute to data quality standards, model documentation, and column-level lineage across our dbt projects
• Support the team in pushing data into business operating systems and AI-powered workflows that help the company function and grow
• Learn and apply best practices around source-of-truth models, metric definitions, and data grain under the guidance of senior engineers
• Use AI to automate analytics engineering processes, reduce toil, and build net-new capabilities for the data organization
• Partner with data platform engineers to help ensure pipelines and data models run reliably in production
• Collaborate with business stakeholders to understand data needs and help translate them into governed, reusable data assets

What we're looking for:

• Experience: 1–2 years as an analytics engineer, data analyst, or in a related technical role
• dbt & SQL: Foundational SQL skills and some exposure to dbt or a modern data stack; a strong desire to develop deep expertise in both
• AI fluency: Curiosity about using AI to move faster, automate processes, and build things that weren't previously possible
• Technical skills: Some familiarity with Python and an eagerness to grow. Basic understanding of schema design and data pipeline concepts
• Business judgment: Interest in understanding how data models serve real business decisions, and how to translate business needs into reliable data
• Semantic precision: Care for writing clear, unambiguous definitions and documentation, for both human and AI consumers of data
• Schedule: Must be able to work Eastern Time hours to support on-call coverage for our data systems

Soft skills and values

• Problem-solving: Curiosity, a bias toward action, and an entrepreneurial approach to building in ambiguous environments
• Communication: Able to translate between technical and business audiences with clarity
• Openness: Receptive to feedback, comfortable questioning assumptions, and resilient when priorities shift
• Planning: Structured thinker who can balance learning fundamentals with near-term delivery