Data Platform Engineering Manager — AI, Self-Serve Infra

Circle; Springfield (IL); On-site; USD 195,000 - 237,000; Full time

Job summary

Circle, a leading internet financial platform, is seeking a Data Platform Engineering Manager to lead a team responsible for ingestion, orchestration, warehouse, BI, and real-time data services. You will own the roadmap, partner on architecture, and work with cross-functional teams including Finance and Risk.

The role emphasizes hands-on leadership, design reviews, and scaling data systems for AI-enabled analytics and governance, with a focus on correctness and security.

Qualifications

• 4+ years managing software engineers, including hiring, performance management, coaching, and senior IC development.
• Hands-on experience building and operating warehouse, orchestration, streaming, or ingestion platforms at scale.
• AI and agentic data systems experience, including LLM-based solutions and evaluation frameworks.
• Clear communicator who writes design docs and explains complex systems to analysts, scientists, engineers, and finance partners.

Responsibilities

• Lead a team of senior data platform engineers, shaping the roadmap and architecture.
• Coach and grow senior ICs into technical leaders and hire effectively.
• Oversee AI-agent management, guardrails, and evaluation standards for data systems.
• Ensure platform is self-service, auditable, and accessible to AI agents with proper access controls.

Skills

Management experience

Data platform engineering

AI/agentic fluency

Self-service platform thinking

Technical leadership

Hands-on debugging

Tools

BigQuery

Airflow

Pub/Sub

Kafka

Iceberg

Job description

Circle, a leading internet financial platform, is seeking a Data Platform Engineering Manager to lead a team responsible for ingestion, orchestration, warehouse, BI, and real-time data services. You will own the roadmap, partner on architecture, and work with cross-functional teams including Finance and Risk.

The role emphasizes hands-on leadership, design reviews, and scaling data systems for AI-enabled analytics and governance, with a focus on correctness and security.