• As a Data Engineer, you will bridge the gap between complex biological science and robust software engineering. • You will be responsible for building the scalable infrastructure that powers our scientific discoveries. • Ensuring that our data pipelines are not only high-performing but also strictly compliant with European data protection standards. • Lead the implementation of challenging features across distributed architectures, ensuring systems are performant, maintainable, and secure. • Design software with built-in resilience and observability; balance immediate product delivery with long-term platform sustainability. • Convert complex scientific requirements into actionable engineering tasks for the development team. • Collaborate with Product, Science, and DevOps to define milestones and ensure projects move from conception to production with measurable impact. • Lead root cause analysis (RCA) for live incidents and implement permanent structural solutions.

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 #: P76450 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

We can only accept candidates based in Ontario or Quebec. The Audio Market Opportunity Modern advertising marketers allocate spending through automated systems that interpret signals. For a channel to capture its fair share of budget, its inventory must be legible to those systems — standardized signals, structured metadata, and machine-readable supply pathways. For the next evolution of media buying, Audience Signal is even more consequential. Agentic buying — autonomous systems that independently interpret objectives, evaluate options, negotiate terms, and execute campaigns — is moving from concept to production. These systems don’t browse inventory the way a human planner does. They query structured environments, evaluate supply through machine-readable signals, and pass over inventory they cannot read. Our Mission Triton Digital builds the infrastructure layer that makes audio inventory legible to modern — and next-generation — advertising markets. Our platform enables broadcasters, independent podcasters, and streaming music services to participate in automated buying on equal terms with the major platforms, aggregating over 100 billion audio impressions per month across podcast, streaming, and broadcast radio inventory. The listener data team is at the heart of that mission. We enrich the listener profile to enable better advertising targeting through services including integration with Data Management Platforms (DMPs), the Profiler, the GeoIP service, and any other systems that serve the goal of making listener audiences continuously discoverable and actionable for buyers. The Role As our MLOps Data Engineer, you’ll be the bridge between data science and production systems — ensuring that models don’t just work in notebooks but thrive in real-world environments. You’ll design and automate CI/CD pipelines, optimize large-scale data processing with Apache Spark, and leverage Databricks to deliver machine learning solutions that are reliable, scalable, and fast. Your work will directly determine how quickly we can turn listener intelligence into structured, queryable signals that advertising systems — today’s DSPs and tomorrow’s agentic buyers — can act on. What You’ll Do - Design, implement, and maintain CI/CD pipelines for machine learning workflows using tools like GitHub Actions, Azure DevOps, or Jenkins. - Build and optimize data processing pipelines in Apache Spark (PySpark and Scala) for large-scale, distributed listener datasets. - Deploy and manage Databricks environments, ensuring efficient cluster usage, job scheduling, and cost optimization. - Collaborate with data scientists to productionize ML models, integrating them into scalable APIs or batch processing systems that feed real-time, machine-readable audience signals. - Implement automated testing, monitoring, and alerting for ML pipelines to ensure the reliability and reproducibility that certified buyers require. - Champion best practices in version control, model registry management, and environment reproducibility. - Help evolve our listener data infrastructure toward agent-compatible supply — live, structured, queryable data feeds that autonomous buying systems can discover and act on without human mediation. What You’ll Bring - Proven experience in Data Engineering, MLOps, and DevOps roles with a focus on automation and scalability. - Strong programming skills in Python, with hands-on experience in Apache Spark. Scala is a huge plus. - Advanced expertise in Databricks, including Delta Lake, structured streaming, feature engineering - Solid understanding of CI/CD principles and tools (e.g., GitHub Actions, Jenkins, Azure DevOps, GitLab CI, ArgoCD). - Familiarity with cloud platforms (AWS, Azure, or GCP) for data and ML workloads. - A problem-solving mindset and the ability to work closely with cross-functional teams. - Strong architectural mindset, capable of evaluating trade-offs across cost, performance, scalability, and maintainability when selecting tools and designing systems. - Experience working with containerized and orchestrated environments (Kubernetes / OpenShift), including deployment, scaling, and fault tolerance of data and ML workloads. - Advanced English required. French is an asset. - Familiarity with IAB data standards, programmatic advertising infrastructure, or AdTech data pipelines is a strong asset. Our benefits package includes - Fully remote position (must be based in ONTARIO or QUEBEC) - 4 weeks of vacation + 5 paid personal days annually - Group insurance programs as of your first day, including access to telemedicine and an EAP - Collective RRSP with matching contribution - Internet reimbursement and more *L’utilisation de l’anglais est nécessaire pour collaborer avec des équipes internes et internationaux, et pour accéder à des informations et des ressources. Triton Digital is an equal opportunity employer committed to fostering a diverse, equitable, and inclusive workplace where all employees are respected, supported, and enabled to perform at their highest potential.

• Design, implement, and maintain CI/CD pipelines for machine learning workflows using tools like GitHub Actions, Azure DevOps, or Jenkins. • Build and optimize data processing pipelines in Apache Spark (PySpark and Scala) for large-scale, distributed listener datasets. • Deploy and manage Databricks environments, ensuring efficient cluster usage, job scheduling, and cost optimization. • Collaborate with data scientists to productionize ML models, integrating them into scalable APIs or batch processing systems that feed real-time, machine-readable audience signals. • Implement automated testing, monitoring, and alerting for ML pipelines to ensure the reliability and reproducibility that certified buyers require. • Champion best practices in version control, model registry management, and environment reproducibility. • Help evolve our listener data infrastructure toward agent-compatible supply — live, structured, queryable data feeds that autonomous buying systems can discover and act on without human mediation.