Analytics Engineer
Listed on 2026-01-03
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IT/Tech
Data Engineer, Data Analyst
Location: Columbia
Overview
Ready to be pushed beyond what you think you’re capable of? At Coinbase, our mission is to increase economic freedom in the world. It’s a massive, ambitious opportunity that demands the best of us, every day, as we build the emerging onchain platform — and with it, the future global financial system.
To achieve our mission, we’re seeking a very specific candidate. We want someone who is passionate about our mission and who believes in the power of crypto and blockchain technology to update the financial system. We want someone who is eager to leave their mark on the world, who relishes the pressure and privilege of working with high caliber colleagues, and who actively seeks feedback to keep leveling up.
We want someone who will run towards, not away from, solving the company’s hardest problems.
Our work culture is intense and isn’t for everyone. But if you want to build the future alongside others who excel in their disciplines and expect the same from you, there’s no better place to be.
While many roles at Coinbase are remote-first, we are not remote-only. In-person participation is required throughout the year. Team and company-wide offsites are held multiple times annually to foster collaboration, connection, and alignment. Attendance is expected and fully supported.
The CX Analytics Engineering team bridges the gap between data engineering, data science, and business analytics by building scalable, impactful data solutions. We transform raw data into actionable insights through robust pipelines, well-designed data models, and tools that empower stakeholders across the organization to make data-driven decisions. As an Analytics Engineer on our team, you will function as a force multiplier, enabling Analytics and Operations to function seamlessly ’ll have the opportunity to translate complex technical and operational requirements into easily consumable front end data solutions, while also heavily influencing the overarching strategy for CX Analytics and its partners.
Our team combines technical expertise with a deep understanding of the business to unlock the full potential of our data. We prioritize data quality, reliability, and usability, ensuring stakeholders can rely on our data to drive meaningful outcomes.
Responsibilities and What You’ll Do- Develop and maintain foundational data models that serve as the single source of truth for analytics across the organization.
- Translate business requirements into scalable data models, dashboards, and tools to empower stakeholders.
- Collaborate with engineering, data science, product, and business teams to ensure alignment on priorities and data solutions.
- Build frameworks, tools, and workflows that maximize efficiency for data users while maintaining high data quality and performance.
- Use modern development and analytics tools to deliver value quickly while ensuring long-term maintainability.
Analytics engineer is a hybrid Data Engineer/Data Scientist/Business Analyst role that understands data flows end to end and can extract value by building data tables or delivering insights.
What You’ll Be Responsible For- Be the expert: quickly build subject matter expertise in a specific business area and data domain; understand data flows from creation, ingestion, transformation, and delivery.
- Interface with stakeholders on data and product teams to deliver the most commercial value from data.
- Collaborate with Engineering and Product partners to deliver data pipelines and insights; fix data gaps for downstream users; take initiative and accountability for issues across the stack.
Build out data models that enable downstream teams to unlock business value through experimentation and analysis. Combine engineering details with statistics and data expertise to improve algorithms. Work with PMs to tie together new product data into a holistic framework to optimize key business metrics.
- Develop new abstractions to support scalable data workflows and internal data apps; stand up a framework for building data apps; use established tools to deliver impact with speed.
- Use core tools (e.g., SQL) to deliver rapid impact when speed is prioritized.
In addition to…
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