Senior Staff Data Engineer

Circle is one of the world’s leading internet financial platform companies, building the foundation of a more open, global economy through digital assets and payment applications. The Senior Staff Data Engineer will define and drive the strategy for data reliability, quality, and operational excellence across the organization, influencing platform and architectural decisions while leading complex data initiatives.

Responsibilities:

• Define and implement organization-wide data quality standards, including data contracts, SLAs, and governance frameworks across domains
• Design and scale reliability and observability frameworks, including SLI/SLO models, lineage tracking, monitoring, and alerting patterns
• Establish and evolve incident management practices, including severity models, escalation paths, on-call structures, and blameless postmortems
• Develop and standardize data engineering SDLC practices, including testing strategies, CI/CD, versioning, and reusable frameworks
• Drive cross-functional prioritization 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

Requirements:

• Extensive experience designing and operating scalable data platforms with a focus on reliability, quality, and observability
• Experience leveraging AI tools and methodologies to design and implement the solutions
• Deep expertise in data architecture, including data modeling, 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, including testing, CI/CD, and development standards for data systems
• Experience building or evolving data platforms in high-growth or highly regulated environments (e.g., fintech, payments, crypto)
• Familiarity with modern data tooling ecosystems, including orchestration, transformation, metadata, and observability platforms
• Experience with technologies such as Astronomer (Airflow), BigQuery, dbt, Dataplex, Kubernetes, and programming languages like Python or Go, or comparable tools in the modern data stack
• Track record of influencing platform strategy, including build vs buy decisions and long-term architectural evolution