We’re partnering with a well-funded and profitable infrastructure-focused fintech company building large-scale identity, risk, and decisioning systems used across highly regulated industries. The platform processes massive volumes of real-time data and powers mission-critical fraud detection and machine learning systems for enterprise customers.

Why This Role Stands Out

This is not a traditional analytics-focused data engineering role. You’ll lead a highly technical platform team responsible for real-time, low-latency data systems that directly power production decisioning, ML infrastructure, and customer-facing products at scale.

The Role

We’re looking for an Engineering Manager to lead a Data Platform team responsible for building and scaling the infrastructure behind real-time data ingestion, processing, storage, and serving systems.

This team owns foundational platform infrastructure that enables machine learning, fraud/risk modeling, internal analytics, and production APIs. You’ll lead engineers working across distributed systems, data infrastructure, and operational platform engineering — helping evolve the company’s next generation of scalable data systems.

This role combines deep technical leadership with people management. You should still enjoy getting into architecture discussions, reviewing systems at depth, and helping solve hard engineering problems, while also mentoring engineers and driving execution across the organization.

This is a remote US-based role.

What You’ll Work On

• Lead and grow a team of engineers focused on scalable data platform infrastructure
• Define technical direction across ingestion, transformation, storage, and serving layers
• Build and evolve batch and real-time data pipelines powering production systems
• Improve reliability, observability, scalability, and performance across platform services
• Partner closely with Data Science, Product, and Engineering teams
• Support ML and decisioning systems with fast, reliable, high-quality data
• Drive operational excellence around monitoring, incident response, and platform reliability
• Establish standards around governance, schema management, and platform architecture
• Mentor engineers while maintaining a high technical hiring bar
• Contribute to system design, architecture reviews, and technical problem solving

Tech Stack

Python, Golang, AWS, PostgreSQL, Redshift, Spark, EMR, Docker, OpenSearch, distributed data systems, real-time processing infrastructure

Ideal Background

• 6–10+ years of experience as a senior/staff-level backend or data-focused engineer
• 2–5+ years of engineering management experience leading platform or data teams
• Strong experience building production-grade data infrastructure and distributed systems
• Experience with low-latency, real-time data platforms and operational data systems
• Background in platform engineering, backend infrastructure, or data-intensive systems
• Strong cloud infrastructure experience (AWS preferred)
• Comfortable operating in fast-paced startup or scale-up environments
• Excellent communication skills with the ability to lead deeply technical discussions
• Hands-on technical mindset despite management responsibilities
• Experience supporting ML, fraud/risk, search, cybersecurity, fintech, or decisioning systems is highly valued

Nice to Have

• Experience with Spark, Kafka, Flink, or streaming infrastructure
• Exposure to ML infrastructure or feature platform systems
• Experience with modern data lake/warehouse architectures
• Fintech, cybersecurity, fraud detection, or highly regulated industry experience
• Prior experience at high-growth B2B infrastructure or platform companies

Compensation & Benefits

• $200,000–$240,000 base salary + equity
• Competitive healthcare coverage for employees and dependents
• 401(k) with company match
• Flexible PTO
• Home office stipend
• Regular in-person company events
• Fully remote flexibility within the US