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.