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 Data Platform team builds and operates systems to centralize all of Coinbase's internal and third-party data, making it easy for teams across the company to access, process, and transform that data for analytics, machine learning, and powering end-user experiences. As an engineer on the team you will contribute to the full spectrum of our systems, from managing foundational processing and data storage, to building and maintaining scalable pipelines, to developing frameworks, tools, and internal applications to make that data easily and efficiently available to other teams and systems. What you’ll be doing (ie. job duties): - Design, build, and operate our foundational data-heavy services: storage (cloud data warehouse, data lake), orchestration (Airflow), batch processing (Spark, SQL), streaming services (Kafka), query federation and caching, time-series db, graph db, and real-time event aggregation stores. - Build and maintain data integration & process SDKs for use by internal services and product teams throughout Coinbase. - Design and build self-service applications to empower our users to manage and troubleshoot their own data pipelines running on our platforms. - Design and build services for end-to-end data security and data observability: managing access controls across multiple storage and access layers, tracking data quality, cataloging datasets and their lineage, usage auditing. - Convert functional requests from data analysts, ML, and security & compliance into reusable and scalable patterns; and assemble data microservices into data platforms for critical business verticals and user cohorts. What we look for in you (ie. job requirements): - You have at least 5+ years of experience in software engineering. - You have Strong Python, Go, or Java backend development skills. - You have general experience working with data systems or data pipelines. - You are familiar with design patterns such as scale-out, caching, key/value, and columnar. - You leverage SQL, Python, Airflow, and BI expertise to analyze data for operational insights. - Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency, cost, and quality. Nice to Have: - Crypto-forward experience, including familiarity with onchain activity such as interacting with Ethereum addresses, using ENS, and engaging with dApps or blockchain-based services Job #: P76805 Pay Transparency Notice: Depending on your work location, the target annual base salary for this position can range as detailed below. Total compensation may also include equity and bonus eligibility and benefits (including medical, dental, vision and 401(k)). Annual base salary range (excluding equity and bonus): $186,065—$218,900 USD Please be advised that each candidate may submit a maximum of four applications within any 30-day period. We encourage you to carefully evaluate how your skills and interests align with Coinbase's roles before applying. Commitment to Equal OpportunityCoinbase is proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, sex, gender expression or identity, sexual orientation or any other basis protected by applicable law. Coinbase will also consider for employment qualified applicants with criminal histories in a manner consistent with applicable federal, state and local law. For US applicants, you may view the Employee Rights and the Know Your Rights notices by clicking on their corresponding links. Additionally, Coinbase participates in the E-Verify program in certain locations, as required by law. Coinbase is also committed to providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process, please contact us at accommodations[at]coinbase.com to let us know the nature of your request and your contact information. For quick access to screen reading technology compatible with this site click here to download a free compatible screen reader (free step by step tutorial can be found here). Global Data Privacy Notice for Job Candidates and ApplicantsDepending on your location, the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available here. By submitting your application, you are agreeing to our use and processing of your data as required. For US applicants only, by submitting your application you are agreeing to arbitration of disputes as outlined here. AI DisclosureFor select roles, Coinbase is piloting an AI tool based on machine learning technologies to conduct initial screening interviews to qualified applicants. The tool simulates realistic interview scenarios and engages in dynamic conversation. A human recruiter will review your interview responses, provided in the form of a voice recording and/or transcript, to assess them against the qualifications and characteristics outlined in the job description. For select roles, Coinbase is also piloting an AI interview intelligence platform to transcribe and summarize interview notes, allowing our interviewers to fully focus on you as the candidate. The above pilots are for testing purposes and Coinbase will not use AI to make decisions impacting employment. To request a reasonable accommodation due to disability, please contact accommodations[at]coinbase.com

Role Description In this role, you will join a player and data analytics team supporting a globally scaled, highly data-driven digital product. You will build and maintain analytics-ready data pipelines, develop well-structured data models, and deliver high-impact data products that enable performance marketing, product insights, and downstream AI/ML use cases. You will act as a bridge between technical data systems and business stakeholders, translating complex signals into trusted, actionable insights. The role emphasizes data quality, reliability, and usability, and offers meaningful ownership in shaping modern analytics solutions at scale. Responsibilities - Partner closely with analysts, data scientists, engineers, and business stakeholders to understand analytics and reporting needs and enable self-service data access. - Build subject matter expertise in relevant business and data domains to ensure accurate interpretation and application of data. - Identify, analyze, and document multi-structured data from diverse sources to support analytics and machine learning requirements. - Design and maintain scalable data models, dataflows, and abstractions that evolve with changing business needs. - Architect, build, and optimize automated data pipelines that transform raw logs and event data into clean, enriched, analytics-ready datasets. - Apply modern analytics and data engineering best practices using object-oriented and modular approaches. - Develop reusable frameworks, standardized components, and new data capabilities to improve system scalability and efficiency. - Enable and enhance performance marketing strategies by delivering robust, reliable data products and insights. - Ensure high standards for data quality, security, and reliability across all solutions. Qualifications - Bachelor’s degree in Computer Science, Software Engineering, or a related technical field with 4+ years of relevant experience OR Master’s degree in a related field with 3+ years of relevant experience OR Equivalent professional experience. - 2+ years of hands-on experience in an analytics engineering or data engineering role supporting business stakeholders. - Strong proficiency in SQL for analytics and data modeling. - Advanced Python skills for data transformation, automation, and pipeline development (4–5+ years). - Experience designing and building data models to support analytics and reporting use cases (3+ years). - Experience working with large-scale data pipelines handling logs and/or event-streaming data. - Hands-on experience with cloud-based data platforms and modern data tools (e.g., Spark, workflow orchestration tools); cloud experience strongly preferred. Preferred Qualifications - Proven ability to deliver analytics solutions and data products that drive measurable business impact. - Experience supporting performance marketing, growth, or digital product analytics use cases (2+ years preferred). - Strong analytical and exploratory skills to evaluate data quality, relevance, and structure. - Solid business acumen with the ability to frame technical solutions around real-world business problems. - Working knowledge of DevOps and/or DataOps practices. - Experience collaborating in cross-functional, product-oriented environments. - Familiarity with the video game or interactive entertainment domain is a plus, whether as an industry professional or experienced player. - Demonstrated critical thinking, problem-solving skills, and a growth-oriented mindset. Salary Range At Blueprint, we strive to offer competitive pay that reflects the value of our team members. Compensation for this role is influenced by a variety of factors, including skills, education, responsibilities, experience, and geographic market. For candidates based in Washington State, the anticipated salary range is $130,000–$140,000 per annum. Please note that we typically do not hire new employees at the top of the posted range. Actual starting pay will be determined based on experience, skills, and internal equity. The final salary and job title may vary depending on the selected candidate’s qualifications and could fall outside the stated range. Equal Opportunity Employer Blueprint Technologies, LLC is an equal employment opportunity employer. Qualified applicants are considered without regard to race, color, age, disability, sex, gender identity or expression, orientation, veteran/military status, religion, national origin, ancestry, marital, or familial status, genetic information, citizenship, or any other status protected by law. If you need assistance or a reasonable accommodation to complete the application process, please reach out to: recruiting@bpcs.com Benefits - Medical, dental, and vision coverage - Flexible Spending Account - 401k program - Competitive PTO offerings - Parental Leave - Opportunities for professional growth and development Location Remote

• Design, develop and maintain scalable and robust data pipelines and ETL processes to support HR modernisation • Collaborate with stakeholders to gather data requirements and translate them into effective technical solutions • Lead migration to cloud-based infrastructure and modernise ETL tools and processes • Work with DevOps aspects of data engineering, including infrastructure setup, configuration, and maintenance using Infrastructure as Code (IaC) • Ensure data quality and governance by implementing frameworks for accuracy, consistency, and compliance • Promote best practices in data engineering and stay up to date with emerging technologies • Mentor junior colleagues • Contribute to broader organisational digitalisation and technical innovation

• Ingest, clean, transform, and structure customer and internally generated engineering data for AI training and inference. • Design and build high-quality mechanical components and assemblies in CAD to serve as authoritative ground truth for evaluating and training AI systems. • Produce labeled datasets, reference designs, annotations, exploded views, sequences, and other engineering artifacts that encode real-world reasoning. • Apply engineering judgment to define and assess output quality across datasets. • Continuously refine standards for metadata, annotation, and model quality, maintaining a living “definition of quality” for ME datasets. • Collaborate with Product Managers to shape tooling used for annotation, data correction, model-output review, and pipeline automation. • Provide detailed feedback on tool usability, workflow efficiency, and automation opportunities. • Help develop scalable, repeatable data processes that improve throughput and data consistency. • Partner closely with engineering and research teams to understand model data requirements, failure modes, and areas needing new data. • Influence model behavior by supplying representative engineering examples and ground-truth mechanical designs. • Partner with customer-facing teams to translate domain requirements, industry standards, and customer data schemas into actionable dataset specifications. • Serve as a subject matter expert on mechanical engineering formats, CAD standards, manufacturing practices, and design artifacts. • Generate technical documentation, exploded views, sequences, and annotations that encode engineering reasoning into training data. • Ensure that datasets reflect real-world constraints, DFM (Design for Manufacturing) considerations, material behavior, and industry best practices. • Embed engineering reasoning into training data so that AI systems learn not just geometry or text, but engineering intent. • Work with customers to understand their data sources, schemas, formats, and quality expectations. • Guide customers in preparing high-quality datasets, defining structured schemas, and improving data pipelines. • Support delivery timelines by communicating progress clearly and surfacing risks or issues early. • Review and work with external contractors, ensuring high-quality output and adherence to SOPs.