Senior Data Engineer

Circle is a financial technology company at the epicenter of the emerging internet of money, where value can finally travel like other digital data — globally, nearly instantly and less expensively than legacy settlement systems. This ground-breaking new internet layer opens up previously unimaginable possibilities for payments, commerce and markets that can help raise global economic prosperity and enhance inclusion. Our infrastructure – including USDC, a blockchain-based dollar – helps businesses, institutions and developers harness these breakthroughs and capitalize on this major turning point in the evolution of money and technology.

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: Multistakeholder, Mindfulness, Driven by Excellence and High Integrity. Circlers are consistently evolving in a remote world where strength in numbers fuels team success. We have built a flexible and diverse work environment where new ideas are encouraged and everyone is a stakeholder.

What you’ll be responsible for:

As a member of the Data Engineering team, you own the data warehouse and pipelines that are used for analytics and reporting. Your work powers Circle business functions, including product development and regulatory reporting for actionable insights and operational excellence, so as to fuel and accelerate business growth. In this role, you will reshape how data moves across the company. High integrity to data accuracy and quality is crucial. Your work will directly impact Circle’s transparency, trust, and accountability needs.

What you'll work on:

• Collaborate with product, engineering, analytics, and finance to design and manage scalable data life cycles.

• Build and maintain ETL/ELT pipelines to source and aggregate the required data for analysis and reporting.

• Parse complex blockchain data, sourced directly from the blockchain and third parties.

• Surface data for internal and customer-facing analytical, financial, and regulatory needs.

• Continually improve data warehouse operations, monitoring, and performance.

• Re-think how data is stored and processed today, within data platforms and outside among Circle business teams and external applications.

• Collaborate on the design, deployment and improvement of a scalable data platform for ingestion, storage, and aggregation.

• Serve as a domain expert in blockchain data modeling, pipelines, quality, and warehousing.

You will aspire to our four core values:

• Multistakeholder - you have dedication and commitment to our customers, shareholders, employees and families and local communities.

• Mindful - you seek to be respectful, an active listener and to pay attention to detail.

• Driven by Excellence - you are driven by our mission and our passion for customer success which means you relentlessly pursue excellence, that you do not tolerate mediocrity and you work intensely to achieve your goals.

• High Integrity - you seek open and honest communication, and you hold yourself to very high moral and ethical standards. You reject manipulation, dishonesty and intolerance.

What you’ll bring to Circle:

For Data Engineer (II)

• 2+ years of data engineering experience with strong data fundamentals.

• Skilled in SQL for data warehouse platforms such as Snowflake, BigQuery, Databricks, and more.

• Proficient in one or more programming languages (Python, Java, Scala).

• Experience with workflow orchestration (Airflow, Dagster, DBT) and cloud platforms (AWS, GCP, Azure).

• Background in blockchain or financial data is a plus.

• Self-starter with a proven ability to learn, collaborate remotely, and communicate effectively in fast-paced environments.

For Senior Data Engineer (III), all the requirements of above and:

• 4+ years of data engineering experience with strong data fundamentals.

• Proficient in SQL within data warehouse systems like Snowflake, BigQuery, Databricks, etc.

• Skilled in building scalable infrastructure to support batch, micro-batch or stream processing for large