Analytics Engineer

Remote: yes Posted: 2026-10-01

As our Analytics Engineer, you'll be the analytical backbone of this ecosystem, combining deep technical craft with strong business partnership to build core data products. Here's what that looks like in practice:

- Own critical products end-to-end - Manage the full lifecycle of warehouse data products and straightforward ingestions, ensuring lineage, PII handling, and auditability are foundational.

- Enable the Data Mesh - Maintain shared dimensional models and central semantic metrics so definitions are registered once and consumed seamlessly across domains.

- Automate regulatory reporting - Build and maintain the robust, highly auditable data models required to automate complex compliance reporting.

- Partner on platform & agentic infrastructure - Guide shared warehouse infrastructure alongside the Data Platform team, and contribute the vital context that internal warehouse maintenance agents depend on.

- Refuse to be a bottleneck - Intervene proactively when you are the sole holder of knowledge, sharing it through rigorous documentation and code review.

Who we're looking for

This role needs someone with a data product owner mindset who thinks beyond the pipeline to the end user, focusing on the decisions they need to make and how the data product unlocks value.

- Technical mastery - Expert in SQL; proficient in Python for scripting, and pipeline work. You are a strong data modeler with experience designing scalable, future-proof models that serve multiple stakeholders and use cases.

- Core tooling - Deep experience with dbt or other semantic modeling tools, familiarity with workflow orchestration, and you treat Git and CI/CD as standard working practice.

- Exceptional communicator - Comfortable presenting methodology and findings to both technical and non-technical partners, including executive leadership. You have a proven ability to drive cross-functional alignment.

- Comfortable with ambiguity - You are a self-starter who takes ownership and drives projects forward with minimal oversight to define the workflows for a brand-new team.

- AI-fluent & curious - You have working fluency with AI-assisted development (Claude, Cursor) and a grounded view of where it adds durable value.

- Nice to haves - Prior experience as a Data Engineer, time spent in FinTech/highly regulated data environments, exposure to LLM tooling built on a data warehouse, or experience with dashboard tools like Looker, Hex, or Tableau.