Director of Engineer

Director of Engineering — FairPlay Sports Media

Department: Technology / Engineering

Reporting to: CTO

Why this role exists

FairPlay Sports Media is building a tech-led, AI- and data-powered sports media network that serves both owned brands (e.g., oddschecker, WhoScored.com, SuperScommesse, and others) and partners with BetTech products spanning data, display, and predictive capabilities.

At FairPlay scale—real-time data, high-frequency updates, and partner integrations—you’ll lead multiple engineering teams to deliver reliable, compliant, high-throughput product execution.

What you’ll do

This role is modelled on modern Director of Engineering expectations:

Your team is your product — you’re accountable for team health, hiring, delivery outcomes, and cross-functional alignment, while remaining technically credible enough to guide architecture and trade-offs.

Lead and grow high-performing teams

• Lead multiple squads through Engineering Managers and senior ICs; build an org that can ship consistently across brands and partner-facing platforms.
• Own hiring strategy and capacity planning, focusing recruitment where it unlocks the most leverage.
• Coach Engineering Managers and senior engineers; create clarity, accountability, and psychological safety.

Own delivery and execution at scale

• Be accountable for predictable delivery of roadmap commitments across BetTech products (Data, Display, Predictive) and shared platform capabilities.
• Increase throughput without sacrificing reliability—improving planning discipline, sequencing, and removing systemic blockers.
• Drive operational excellence for high-traffic, high-frequency systems (e.g., real-time odds/pricing and rapid data updates).

Build strong cross-functional and partner interfaces

• Create a consistent, high-trust interface between Engineering and Product (and, as needed, Commercial/Partnerships), translating strategy into executable plans.
• Partner closely with data/AI stakeholders—especially as FairPlay expands predictive AI, pricing, and behavioral data-led products through FairPlay Technologies / FairPlay AI.
• Enable partner integrations and “white-label” deployments where required, ensuring a smooth path from contract → integration → measurable value.

Set technical direction (without being the bottleneck)

• Guide architectural decisions across APIs, data pipelines, ML-enabled products, and front-end components/widgets—ensuring systems are secure, observable, and cost-effective.
• Sponsor engineering-wide standards where helpful, while allowing local variation where it accelerates outcomes.
• Ensure engineering practices cover the full DevOps lifecycle and modern CI/CD expectations.

Run the org with measurable outcomes

• Define, measure, and improve the metrics that matter (delivery, reliability, quality, and org health).
• Establish lightweight governance: clear ownership, incident learnings, technical debt management, and documentation that stays current.

What success looks like (example performance indicators)

• Hiring actual vs. plan for critical teams/skills.
• Delivery throughput & predictability: roadmap commitments met with stable scope/quality.
• Cycle time / lead time: reduced time from idea → production; fewer blocked work items.
• Reliability: improved uptime, incident rates, and mean time to restore (MTTR), especially for real-time feeds and partner-facing APIs.
• Data & latency SLAs: sustained performance at high-frequency update rates and real-time pricing/odds experiences.
• Documentation/operational readiness: runbooks, on-call hygiene, and key technical docs kept current.

What we’re looking for:

Required experience

• Proven experience leading multiple engineering teams (typically via Engineering Managers) in a product-led, high-availability environment.
• Strong systems and architecture judgment—able to broker high-level technical decisions and trade-offs across teams.
• Solid grasp of the DevOps lifecycle and delivery automation (CI/CD), with a track record of improving engineering productivity.
• Experience building platforms or products that integrate with external partners (APIs, SDKs, embeddable components), ideally in data-rich domains.

Nice to have

• Experience in regulated or compliance-sensitive markets (or adjacent industries) with strong operational discipline.
• Exposure to data/ML product delivery (feature pipelines, model deployment patterns, experimentation frameworks), especially where AI-driven insights are core to the product.
• Familiarity with high-traffic consumer products alongside B2B SaaS/partner distribution models.

Working style

• You bring clarity to ambiguous problems and drive execution/direction across functions.
• You communicate well up and down the org—aligning exec stakeholders while staying close enough to the work to unblock teams quickly.
• You care deeply about building a healthy, inclusive engineering culture where teams can do the best work of their careers.