Senior Staff Data Engineer

About Circle Circle is a global financial technology company at the forefront of the new internet of money. Circle's infrastructure, including USDC, a blockchain-based dollar, powers payments, commerce, and financial applications worldwide. Circle helps businesses, institutions, and developers leverage breakthrough blockchain technologies to drive global economic prosperity and digital inclusion. About the Role This is not a traditional pipeline-building or warehouse-focused Data Engineer role. Circle is looking for a Senior Staff IC who will define and drive the long-term strategy for data reliability, quality, and operational excellence across the organisation, shaping how Circle builds, governs, and trusts its data ecosystem. The central question is whether this person can identify systemic weaknesses in a complex data ecosystem and create the frameworks, standards, architecture, and operating mechanisms that prevent entire classes of failures across multiple teams. If the answer is primarily that they can build very sophisticated pipelines, this is not the right hire. Key Responsibilities - Establish company-wide standards for data quality, contracts, ownership, and governance, driving adoption across producer and consumer teams - Design and lead scalable reliability and observability frameworks (SLIs/SLOs, freshness and availability targets, alerting strategy, incident response, error budgets) - Drive cross-functional prioritisation of reliability initiatives, balancing technical debt, operational health, and product delivery across teams - Lead ecosystem-wide platform improvements, identifying architectural gaps, reducing fragmentation, and influencing build-vs-buy decisions - Own and deliver complex, high-impact data initiatives, aligning stakeholders, mitigating risks, and driving scalable solutions in ambiguous environments - Mentor senior engineers and become the technical point person for ambiguous, cross-cutting data problems Requirements - Extensive experience designing and operating scalable data platforms with a focus on reliability, quality, and observability - Deep expertise in data architecture: data modelling, pipeline design, and distributed data systems - Proven ability to define and implement data quality frameworks, including SLAs, data contracts, and governance standards - Strong experience establishing SLI/SLO frameworks, monitoring, and alerting for large-scale data systems - Demonstrated ability to lead complex, cross-team technical initiatives and drive alignment across stakeholders - Experience defining and scaling engineering best practices: testing, CI/CD, and development standards for data systems - Experience leveraging AI tools and methodologies to design and implement solutions Bonus Skills - Experience building or evolving data platforms in high-growth or highly regulated environments (fintech, payments, crypto) - Familiarity with modern data tooling: orchestration (Astronomer/Airflow), transformation (dbt), warehouses (BigQuery), metadata and lineage (Dataplex, DataHub, Amundsen), observability (Monte Carlo, Great Expectations) - Hands-on with Kubernetes, Terraform, streaming platforms (Kafka), Python or Go - Track record of influencing platform strategy: build-vs-buy decisions and multi-year architectural evolution - Ledger, reconciliation, settlement, or regulatory reporting experience