Coinbase
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. We’re seeking a candidate 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, who thrives under pressure, and who actively seeks feedback to level up. We want someone who will run toward solving the company’s hardest problems. Our work culture is intense and isn’t for everyone. If you want to build the future alongside others who excel in their disciplines, 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, with team and company-wide offsites held multiple times annually to foster collaboration, connection, and alignment. Attendance is expected and supported. The CX Analytics Engineering team bridges 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 to make data-driven decisions. As an Analytics Engineer, you will enable Analytics and Operations to function at scale and translate complex technical and operational requirements into easily consumable front-end data solutions, while influencing the overarching strategy for CX Analytics and its partners. We prioritize data quality, reliability, and usability to ensure stakeholders can rely on data to drive meaningful outcomes. What We Do
Trusted Data Sources: Develop and maintain foundational data models that serve as the single source of truth for analytics across the organization. Actionable Insights: Translate business requirements into scalable data models, dashboards, and tools for stakeholders. Cross-Functional Collaboration: Partner with engineering, data science, product, and business teams to align on data solutions and priorities. Scalable Data Products: Build frameworks, tools, and workflows that maximize efficiency for data users while maintaining data quality and performance. Outcome-Focused Solutions: Use modern development and analytics tools to deliver value quickly with long-term maintainability. What You’ll Be Doing
Analytics engineer is a hybrid Data Engineer/Data Scientist/Business Analyst role with end-to-end data flow understanding and the engineering toolkit to extract value indirectly (building tables) or directly (solving problems, delivering insights). Expectations 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. Examples: Step into a new line of business and work with Engineering and Product partners to deliver first data pipelines and insights. Communicate with engineering teams to fix data gaps for downstream data users. Take initiative and accountability for fixing issues anywhere in the stack. Generate business value: Interface with stakeholders on data and product teams to deliver the most commercial value from data (directly or indirectly). Examples: Build a new data model allowing multiple downstream DS teams to unlock value through experimentation and ad hoc analysis. Combine engineering details of the algo engine with stats and data expertise to improve the algo. Work with PMs to integrate new x-PG and x-Product data into one holistic framework to optimize key financing product business metrics. Focus on outcomes not tools: Use various frameworks to identify the best-fit tools to deliver value. Examples: Develop abstractions (e.g., UDFs, Python packages, dashboards) to support scalable data workflows/infra. Stand up a framework for building data apps internally to enable other teams to quickly add value. Use established tools (e.g., SQL) to deliver impact when speed is top priority. What We Look For In You
Beyond out-of-the-box thinking, attention to detail, a sense of urgency, and autonomy, we expect the following skills: Customer Support Data Experience: Familiarity with data elements and processes supporting Customer Support initiatives, including employee performance monitoring, staffing inputs, and handling of sensitive PII across stakeholders. Data Modeling Expertise: Strong understanding of modular, reusable data models (e.g., star/snowflake schemas). Prompt Design and Engineering: Expertise in prompt engineering for large language models, including creating and refining prompts to improve accuracy and performance for internal tools. Advanced SQL: Proficiency in advanced SQL techniques for transformation, querying, and optimization. Intermediate to Advanced Python: Scripting, automation, OOP, and scalable frameworks. Collaboration and Communication: Ability to translate technical concepts into business value and manage projects across teams. Data Pipeline Development: Experience building and maintaining ETL/ELT pipelines with tools like dbt, Airflow, or similar. Data Visualization: Proficiency in dashboards with Looker, Tableau, Superset, or Python libraries. Development Tools: Familiarity with GitHub, CI/CD, and modern workflows. Data Architecture: Knowledge of data lake/warehouse architectures (e.g., Snowflake, Databricks) and transformations. Business Acumen: Ability to address business challenges through analytics engineering. Data Savvy: Familiarity with statistics and probability. Bonus Skills: Cloud platforms (AWS, GCP); Docker or Kubernetes. Position ID: G2754 Pay Transparency Notice: The target annual salary for this position varies by location. Full-time offers include target bonus and benefits (medical, dental, vision, 401(k)). Pay Range: $207,000—$244,100 USD Please be advised that each candidate may submit a maximum of four applications within any 30-day period. Evaluate alignment with Coinbase roles before applying. Commitment to Equal Opportunity: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, gender, national origin, age, disability, veteran status, sex, gender identity or expression, sexual orientation, or any other protected status. For US applicants, you may view the Employee Rights and Know Your Rights notices, and Coinbase participates in the E-Verify program where required. Disability accommodation requests: If you need a reasonable accommodation, contact accommodations@coinbase.com. For accessibility, download or access a screen reader since the site supports compatibility. Global Data Privacy Notice: Depending on location, GDPR/CCPA may regulate data handling. Our full notice is available here. By submitting your application, you agree to data processing as required. For US applicants, arbitration of disputes may apply as described here. AI Disclosure: For select roles, Coinbase pilots AI tools for initial screening. A human recruiter will review responses. Some roles may use an AI interview intelligence platform for transcription and summarization of interview notes. These pilots are for testing and will not be used to make hiring decisions.
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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. We’re seeking a candidate 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, who thrives under pressure, and who actively seeks feedback to level up. We want someone who will run toward solving the company’s hardest problems. Our work culture is intense and isn’t for everyone. If you want to build the future alongside others who excel in their disciplines, 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, with team and company-wide offsites held multiple times annually to foster collaboration, connection, and alignment. Attendance is expected and supported. The CX Analytics Engineering team bridges 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 to make data-driven decisions. As an Analytics Engineer, you will enable Analytics and Operations to function at scale and translate complex technical and operational requirements into easily consumable front-end data solutions, while influencing the overarching strategy for CX Analytics and its partners. We prioritize data quality, reliability, and usability to ensure stakeholders can rely on data to drive meaningful outcomes. What We Do
Trusted Data Sources: Develop and maintain foundational data models that serve as the single source of truth for analytics across the organization. Actionable Insights: Translate business requirements into scalable data models, dashboards, and tools for stakeholders. Cross-Functional Collaboration: Partner with engineering, data science, product, and business teams to align on data solutions and priorities. Scalable Data Products: Build frameworks, tools, and workflows that maximize efficiency for data users while maintaining data quality and performance. Outcome-Focused Solutions: Use modern development and analytics tools to deliver value quickly with long-term maintainability. What You’ll Be Doing
Analytics engineer is a hybrid Data Engineer/Data Scientist/Business Analyst role with end-to-end data flow understanding and the engineering toolkit to extract value indirectly (building tables) or directly (solving problems, delivering insights). Expectations 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. Examples: Step into a new line of business and work with Engineering and Product partners to deliver first data pipelines and insights. Communicate with engineering teams to fix data gaps for downstream data users. Take initiative and accountability for fixing issues anywhere in the stack. Generate business value: Interface with stakeholders on data and product teams to deliver the most commercial value from data (directly or indirectly). Examples: Build a new data model allowing multiple downstream DS teams to unlock value through experimentation and ad hoc analysis. Combine engineering details of the algo engine with stats and data expertise to improve the algo. Work with PMs to integrate new x-PG and x-Product data into one holistic framework to optimize key financing product business metrics. Focus on outcomes not tools: Use various frameworks to identify the best-fit tools to deliver value. Examples: Develop abstractions (e.g., UDFs, Python packages, dashboards) to support scalable data workflows/infra. Stand up a framework for building data apps internally to enable other teams to quickly add value. Use established tools (e.g., SQL) to deliver impact when speed is top priority. What We Look For In You
Beyond out-of-the-box thinking, attention to detail, a sense of urgency, and autonomy, we expect the following skills: Customer Support Data Experience: Familiarity with data elements and processes supporting Customer Support initiatives, including employee performance monitoring, staffing inputs, and handling of sensitive PII across stakeholders. Data Modeling Expertise: Strong understanding of modular, reusable data models (e.g., star/snowflake schemas). Prompt Design and Engineering: Expertise in prompt engineering for large language models, including creating and refining prompts to improve accuracy and performance for internal tools. Advanced SQL: Proficiency in advanced SQL techniques for transformation, querying, and optimization. Intermediate to Advanced Python: Scripting, automation, OOP, and scalable frameworks. Collaboration and Communication: Ability to translate technical concepts into business value and manage projects across teams. Data Pipeline Development: Experience building and maintaining ETL/ELT pipelines with tools like dbt, Airflow, or similar. Data Visualization: Proficiency in dashboards with Looker, Tableau, Superset, or Python libraries. Development Tools: Familiarity with GitHub, CI/CD, and modern workflows. Data Architecture: Knowledge of data lake/warehouse architectures (e.g., Snowflake, Databricks) and transformations. Business Acumen: Ability to address business challenges through analytics engineering. Data Savvy: Familiarity with statistics and probability. Bonus Skills: Cloud platforms (AWS, GCP); Docker or Kubernetes. Position ID: G2754 Pay Transparency Notice: The target annual salary for this position varies by location. Full-time offers include target bonus and benefits (medical, dental, vision, 401(k)). Pay Range: $207,000—$244,100 USD Please be advised that each candidate may submit a maximum of four applications within any 30-day period. Evaluate alignment with Coinbase roles before applying. Commitment to Equal Opportunity: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, gender, national origin, age, disability, veteran status, sex, gender identity or expression, sexual orientation, or any other protected status. For US applicants, you may view the Employee Rights and Know Your Rights notices, and Coinbase participates in the E-Verify program where required. Disability accommodation requests: If you need a reasonable accommodation, contact accommodations@coinbase.com. For accessibility, download or access a screen reader since the site supports compatibility. Global Data Privacy Notice: Depending on location, GDPR/CCPA may regulate data handling. Our full notice is available here. By submitting your application, you agree to data processing as required. For US applicants, arbitration of disputes may apply as described here. AI Disclosure: For select roles, Coinbase pilots AI tools for initial screening. A human recruiter will review responses. Some roles may use an AI interview intelligence platform for transcription and summarization of interview notes. These pilots are for testing and will not be used to make hiring decisions.
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