Data Platform Engineering Manager

Job Description

Job Description

Octagon Talent Solutions is a full-service technology recruitment and staffing company based in South Florida. We humanize technical recruitment by identifying candidates' long-term career goals and assessing cultural fit when presenting opportunities. Our focus on long-term relationships helps ensure placements that last.

Job Overview:

One of our explosively growing clients is building the future of identity verification and fraud detection, powering real-time decisions for many of the largest financial institutions in the U.S. Octagon Talent Solutions is in search of a Data Platform Engineering Manager to lead a team responsible for the data infrastructure that underpins their products and decisioning systems, spanning ingestion, transformation, storage, and low-latency serving. This is a fully remote (US-based) role with high ownership, meaningful technical depth, and a direct impact on how we detect and prevent identity fraud at scale.

RESPONSIBILITIES:

• Lead, mentor, and grow a high-performing Data Platform team (currently ~7 engineers, expanding).
• Set technical direction and drive architecture for real-time and batch data systems—ingestion, processing, storage, and serving.
• Partner closely with Data Science, Product, and Engineering to ensure data is reliable, accessible, and actionable across the business.
• Establish and reinforce best practices for data quality, observability, governance, and schema management.
• Improve platform performance, scalability, and cost efficiency in collaboration with Infrastructure/Platform teams.
• Build an execution culture of ownership and accountability (monitoring, alerting, incident response, and continuous improvement).
• Contribute hands-on when needed through design reviews, technical deep-dives, and problem-solving in complex systems.
• Maintain a high hiring bar and help scale the team with thoughtful recruiting and onboarding.

REQUIREMENTS:

• 2–5+ years of engineering management experience leading data/platform/backend teams (with strong people leadership).
• Prior experience as a senior/staff-level data engineer or backend engineer with a strong data focus; still able to go deep “in the weeds” when required.
• Proven track record building real-time, low-latency production systems where data is accurate, controllable, and served quickly to downstream systems.
• Strong fundamentals in system design, distributed systems, and operational reliability.
• Experience with modern cloud data platforms and architectures (AWS preferred).
• Proficiency in Python, Golang, or similar languages; comfortable reviewing and guiding production-quality code.
• Strong SQL and data modeling knowledge; experience with relational databases and warehouses.
• Startup or growth-stage experience; comfortable operating in a fast-paced, high-ownership environment.

Nice to have: Spark/EMR, Kafka/Flink, Redshift, OpenSearch, Docker/containerized deployments, and experience supporting ML or fraud/risk systems.