Engineering Manager, Data Platform (Remote)

Map Ssg

1d•Remote

About The Position

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. 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.

Requirements

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

Nice To Haves

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
Experience supporting ML, fraud/risk, search, cybersecurity, fintech, or decisioning systems

Responsibilities

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