Senior Manager, Data Engineering

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:

As a Senior Data Engineering Manager at Circle, you will lead the whole Data Engineering organization at Circle. You will be responsible for setting the vision for the team, defining a strategy, prioritizing the work and driving execution at a high level while fostering a culture of trust, empathy, and technical excellence. You will own the data warehouse and pipelines that power a myriad of domains including product analytics, blockchain analytics, finance, marketing, risk among others. You will ensure the team’s solutions are reliable, scalable, and impactful. Your leadership will enable Circle’s product, analytics, and operational teams to generate actionable insights, make informed decisions, automate processes and leverage agentic AI. In addition to managing and mentoring the team, you will serve as a strong technical leader — capable of executing hands-on when needed, providing architectural guidance and reviewing your team member’s technical work.

What you'll work on:

• Lead, mentor, and grow a team of data engineers (including staff / sr staff engineers and managers), supporting their career development and ensuring high-quality, timely delivery.

• Partner with data analysts, data scientists, domain SMEs, data platform engineers, software engineers among other XFN partners to deliver trustworthy, actionable data for decision-making.

• Serve as a hands-on technical leader by participating in code reviews, design reviews, and architectural decisions.

• Drive the long-term vision for Circle’s data engineering practices, balancing innovation with operational excellence.

• Explore and leverage AI-driven approaches to improve development efficiency and modernize workflows.

• Enable Agentic AI solutions to leverage data across Circle.

What you’ll bring to Circle:

• 5+ years of direct people management experience, with a track record of coaching, mentoring, and growing data engineers, including very senior individual contributors and/or people managers.

• 10+ years of hands-on data experience with strong data architecture, modeling, and pipeline development skills. Current hands on experience.

• Deep proficiency in SQL within modern data warehouse environments (Snowflake, BigQuery, Databricks, etc.).

• Proficiency in one or more programming languages (Python, Java, Scala), with the ability to guide and review technical work.

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

• Experience in data provenance, governance, and big data technologies (including open-source solutions).

• Strong cross functional partnership and conflict management skills.

• Background in blockchain or financial data is a plus.

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 comp