Circle (NYSE: CRCL) is one of the world’s leading internet financial platform companies, building the foundation of a more open, global economy through digital assets, payment applications, and programmable blockchain infrastructure. Circle’s platform includes the world’s largest regulated stablecoin network anchored by USDC, Circle Payments Network for global money movement, and Arc, an enterprise-grade blockchain designed to become the Economic OS for the internet. Enterprises, financial institutions, and developers use Circle to power trusted, internet-scale financial innovation. Learn more at circle.com.
What you’ll be part of:
Circle is committed to visibility and stability in everything we do. As we grow as an organization, we're expanding into some of the world's strongest jurisdictions. Speed and efficiency are motivators for our success and our employees live by our company values: High Integrity, Future Forward, Multistakeholder, Mindful, and Driven by Excellence. We have built a flexible work environment where new ideas are encouraged and everyone is a stakeholder.
What You’ll Be Responsible For Circle’s Data Platform team builds and operates the foundation that every analytics, monitoring, compliance and data-focused AI workload at Circle runs on: ingestion of production databases, product events, third-party sources and blockchain data across dozens of networks into a company-wide warehouse. We own the orchestration platform that runs thousands of pipelines, the BI layer, real-time event and transaction monitoring services, and the data assets and agent interfaces that let people and AI agents ask questions of Circle’s data and trust the answers.
As the DP Engineering Manager, you will lead a team of senior data platform engineers through the next chapter of this platform: ensuring it is correct by construction, self-service by default, and usable by AI agents with the proper access controls and audit trails. This is a hands-on technical leadership role. You will own the roadmap, partner with our Staff Engineer to own the architecture, manage and grow the team, partner with Data Engineering, Data Science, Analytics, Product Engineering, Finance, Compliance and Risk, and stay close to the systems through design reviews, code reviews, incident response and the occasional prototype.
What You’ll Work On
- Own the vision, architecture, and roadmap for Circle’s ingestion, orchestration, warehouse, BI, and real-time data services. Prioritize trade-offs clearly.
- Manage, coach, and grow senior engineers. Develop senior ICs into technical leaders and hire well.
- Lead AI-agent management, guardrails, and review standards. Hold agent output to a human engineer’s quality bar.
- Treat datasets as AI infrastructure. Curate, version, and govern training, fine-tuning, and evaluation sets with provenance, labeling workflows, access controls, and deterministic reproducibility.
- Use AI to multiply team output. Equip engineers with agentic tools for design, coding, testing, on-call, and documentation; measure the gains.
- Make correctness and data quality platform features through SLOs, data contracts, lineage, automated checks, and clear dataset ownership.
- Build the platform’s AI and agentic layer: metadata, semantic context, natural-language access to canonical data, pipeline and on-call agents, and deterministic, auditable evaluations within existing access controls.
- Make the platform self-service. Let Data Engineering and product teams onboard sources, pipelines, dashboards, and monitoring rules without filing tickets.
- Operate a reliable production platform with clear SLAs, cost attribution, budget planning, vendor upgrades with rollback plans, and honest status reporting.
- Partner with Data Engineering, Data Science, Analytics, Product Engineering, Security, TechOps, and Finance to build reusable platform capabilities - not one-off pipelines.
- Stay close to the code: lead designs, review critical paths, debug production issues, and prototype when it accelerates progress.
What You’ll Bring to Circle Core Requirements
- Experienced manager. 4+ years managing software engineers, including hiring, performance management, coaching, and senior IC development; 6+ years in data, ML, and/or platform engineering.
- Deep data platform experience. Hands-on experience building and operating warehouse, orchestration, streaming, or ingestion platforms at scale. Examples include BigQuery, Airflow, Pub/Sub, Kafka, and Iceberg - or equivalents.
- Correctness and quality mindset. Defined and met data SLOs, built validation that caught real problems, and changed architecture when data was wrong, late, or untrusted.
- AI and agentic fluency. Built or led LLM-based or agentic data systems, such as natural-language analytics, semantic layers, pipeline agents, or evaluation frameworks. Can keep them within existing data access controls.
- Self-service and platform thinking. Designed a platform other teams use, driven adoption, measured fewer bespoke requests, and know what you would change next time.
- Technical leadership. Owned high-impact platform projects end to end, with a track record of successful releases.
- Hands-on. Read code and designs critically, debug difficult pipeline or warehouse issues, and recently designed, prototyped, reviewed, or shipped production code.
- Clear communicator and collaborator. Write design documents people use, explain complex systems to analysts, scientists, engineers, and finance partners, and give leaders direct recommendations.
- AI fundamentals. Understand model training and evaluation. Have built or used datasets by cleaning training and fine-tuning corpora, creating labeled evaluation sets, versioning data, and measuring its impact on model quality. Know how to prevent label noise, leakage, and distribution drift.
Preferred Requirements
- Experience with blockchain data at scale: indexing many networks, handling chain reorganizations, reconciling balances, and serving near-real-time on-chain event monitoring
- Experience in fintech, crypto, payments or another regulated environment where auditability, restricted data handling and operational controls are part of the platform
- Experience with streaming and stateful processing for transaction-centric, low-latency monitoring
- Familiarity with data catalog and lineage tooling, access governance on a cloud warehouse, and cost attribution for shared compute
- Experience with Python, Go or Java services, and with agent frameworks and protocols such as LangGraph or MCP
- Experience leading a geographically distributed team
Circle is on a mission to create an inclusive financial future, with transparency at our core. We consider a wide variety of elements when crafting our compensation ranges and total compensation packages.
Starting pay is determined by various factors, including but not limited to: relevant experience, skill set, qualifications, and other business and organizational needs. Please note that compensation ranges may differ for candidates in other locations.
Base Pay Range: $195,000 - $236,667 We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status, or any other protected status required by the laws in the locations where we hire. Additionally, Circle participates in the E-Verify Program in certain locations, as required by law.
Should you require accommodations or assistance in our interview process because of a disability, please reach out to accommodations@circle.com for support. We respect your privacy and will connect with you separately from our interview process to accommodate your needs.
