• Design, develop, and maintain scalable and reliable data pipelines • Build and optimize ETL/ELT processes to ingest data from multiple sources • Develop and manage data models in BigQuery to support analytics and reporting • Implement automated workflows and scheduling using Airflow • Ensure data quality, integrity, and performance across pipelines • Collaborate with cross-functional teams to gather requirements and deliver data solutions • Apply CI/CD best practices to support efficient and reliable deployments • Troubleshoot and resolve data pipeline and performance issues

• Work on a project for data migration and quality initiative • Prepare, cleanse, and reconcile data across systems • Ensure a clean, consistent, and compliant dataset • Collaborate with a team that values rigour and precision

• Design, develop, and maintain scalable data ingestion pipelines to onboard structured, semi-structured, and unstructured data from batch and streaming sources (e.g., APIs, databases, flat files, message queues) into the Azure/Databricks environment. • Implement de-duplication strategies across large-scale datasets using deterministic and probabilistic matching techniques to ensure data integrity and reduce redundancy within the Data Lake. • Develop and enforce data tagging frameworks to classify, label, and annotate datasets with appropriate metadata (e.g., sensitivity, source, domain, lineage) to support data governance, discoverability, and compliance requirements. • Assist with Operationalizing deployments and support of Cloud services for ETL Operations. • This will include standardizing and automating processes and workflows, creating documentation/knowledge articles, and overall assisting Operations staff who have limited experience in Cloud. • Written and oral presentations to high-level CIO management on status of current efforts. • Possesses skills and experience related to business management, systems engineering, operations research, and management engineering. • Typically has specialization in a particular technology or business application. • Keeps abreast of technological developments and industry trends. • Assist with deployment, configuration, and management of Azure Cloud environment. • Assist with migration efforts of existing ETL jobs into Azure/Databricks cloud environment. • Ability to share optimization and efficiencies with the larger team and management. • Ability to automate solutions to repetitive problems/tasks.

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 You will define and drive the strategy for data reliability, quality, and operational excellence across the organization, shaping how Circle builds and trusts its data ecosystem. This includes establishing company-wide standards for data quality, contracts, and governance; designing scalable reliability and observability frameworks; and institutionalizing incident management practices that promote a culture of accountability and continuous improvement. You will influence platform and architectural decisions to ensure long-term scalability, reduce systemic risk, and eliminate classes of failure across the data landscape. As a senior technical leader, you will also guide cross-team prioritization of reliability investments, define best-in-class data engineering practices, and lead complex, high-impact initiatives in ambiguous environments-driving alignment, mitigating risk, and delivering robust, scalable data solutions. What you'll work on - 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 What you'll bring to Circle Core 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 Preferred Requirements - 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 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: $225,000 - $290,000 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. #LI-Remote