Job Description
Job Requirements
About the Talent Data Platform
The Talent Data Platform (TDP) is Phenom's foundational data infrastructure the central nervous system that unifies identity resolution, profile management, behavioral signals, and real-time segmentation across every product surface. TDP handles the full complexity of talent data: leads, candidates, and employees flowing through applications, assessments, interviews, offers, background checks, and onboarding all with rigorous data governance and compliance. This is the platform other teams build on.
About The Role
We're looking for an Engineering Manager to own and grow the TDP engineering organization. You'll lead a team of engineers building distributed systems. You will define the technical roadmap, make consequential architectural decisions, hire and develop engineers, and ship platform capabilities that directly unlock product experiences for millions of talent interactions. You'll operate at the intersection of distributed systems engineering, data platform design, and talent acquisition domain expertise.
You'll be both a technical leader and a people leader someone who can dive into merge/unmerge event semantics in a design review, then context-switch to coaching an engineer through a career conversation, and then represent TDP's strategic direction to executive stakeholders.
What You'll Do
Own the platform, end to end. Define and drive the multi-quarter technical roadmap for TDP. Identify what needs to be built, in what order, and why then execute against it with your team. You won't wait for requirements to be handed down; you'll spot the gaps, propose the solutions, and drive consensus across product, engineering, and leadership.
Build and lead a high-performing team. Hire, develop, and retain engineers who thrive on hard problems in distributed systems and data infrastructure. Set clear expectations, provide direct and constructive feedback, and create an environment where engineers ship great work and grow in their careers.
Drive technical excellence. Set the bar for system design, code quality, reliability, and operational maturity. Guide your team through the complexities of event-driven architectures, identity resolution at scale, and the tradeoffs inherent in building a platform that must be both flexible and correct.
Run the team on metrics. Define and own a weekly scorecard of input and output metrics for the TDP team this is a core pillar of how Phenom executes. You'll run a weekly metrics review where the team inspects both, connects deviations in outputs back to specific input metric misses, and commits to corrective actions with owners and deadlines. When an output metric degrades say, data freshness SLA drops you won't treat it as an isolated incident; you'll trace it to which input metrics slipped and fix the upstream cause. You'll publish a weekly metrics summary to leadership so there are no surprises. And you'll evolve the scorecard as the platform matures retiring metrics that go consistently green and introducing new ones as TDP moves from infrastructure buildout to segmentation to activation to intelligence.
Ship with velocity by rethinking how software gets built. Continuously improve your team's engineering processes, tooling, and development workflows. Evaluate and adopt modern approaches to accelerate the software development lifecycle including leveraging AI-assisted development, automated code generation, and intelligent testing where they genuinely compress cycle times without sacrificing quality. Build a team culture that is curious about emerging tools and pragmatic about adopting them.
Collaborate across Phenom. TDP is a platform team your customers are internal product teams building Career Sites, CRM, Integrations, Internal Mobility, and AI Matching. You'll partner closely with these teams to understand their data access patterns, define APIs and event contracts, and ensure TDP enables rather than blocks their roadmaps.
Champion data governance and compliance. Ensure TDP meets enterprise-grade requirements for GDPR, consent management, data residency, and audit trails. Talent data is sensitive the platform must be trustworthy by design.
What We're Looking For
8+ years of software engineering experience, with deep hands-on work in distributed systems, data platforms, or backend infrastructure. You've built and operated systems involving stream processing, event-driven architectures, or large-scale data pipelines.
1+ years leading engineering teams, with demonstrated ability to hire well, develop people, set technical direction, and deliver results through others. You've managed teams of 5-12 engineers and have a track record of building teams that ship reliably.
Strong architectural judgment across the data platform stack. You're fluent in technologies like Kafka, Flink, Spark, or equivalent stream/batch processing systems. You have working knowledge of storage engines (column stores, key-value stores, search engines) and can reason about tradeoffs between consistency, latency, and throughput.
Metrics-driven management discipline. You've built and operated weekly input/output metric scorecards for engineering teams not as a reporting exercise, but as the primary mechanism for steering execution. You've used input metrics to diagnose output problems before they escalate, and you've built the habit of weekly inspection and course-correction into your team's operating rhythm. You believe that if you can't measure it weekly, you can't improve it weekly.
Ability to build and operate with AI in the loop. You have a point of view on where LLMs and AI agents create real leverage in the engineering workflow from code generation and review to test automation, entity extraction, and signal computation. You've experimented with these tools yourself and can guide your team on where they help versus where they add noise. Ideally, you've built or contributed to systems that embed AI capabilities as first-class components, not just as add-ons.
Bias toward action and ownership. You don't wait for permission or perfect information. When you see a problem whether it's a technical gap, a process bottleneck, or an organizational misalignment you move to fix it. You take accountability for outcomes, not just effort.
Comfort with ambiguity at the platform layer. You've worked in domains where the requirements aren't always crisp where you need to understand customer problems deeply, make judgment calls about what to build, and iteratively refine as you learn.
Strong communication skills. You can explain complex platform concepts to non-technical stakeholders, write clear technical documents, and represent your team's work and strategy to executive leadership.
