Director Of Engineering - Data Platform

Job Overview:

Our Client is seeking a Director of Engineering to lead the Data Platform organization at the core of its AI-driven cybersecurity products. This role owns the ingestion, processing, storage, and analysis of petabytes of security telemetry - spanning network packets, logs, identity signals, and security events - and advances the platform to power modern AI workloads, autonomous security workflows, and next-generation analytics.

This is an organizational leadership role that demands deep technical credibility. You will build and develop high-performing, distributed teams while engaging directly in architectural decisions, challenging assumptions, and de-risking designs. Partnering closely with Product, Security Research, AI, Infrastructure, and Customer teams, you will establish a platform-first strategy that accelerates Data Science, AI/ML, and product delivery through self-service capabilities, strong observability, and best-in-class reliability.

Job Responsibilities:

• Build, grow, and mentor high-performing engineering teams across multiple geographies
• Develop engineering managers and senior technical leaders through coaching, sponsorship, and career development
• Foster an inclusive culture grounded in trust, ownership, and accountability
• Create conditions for strong execution with clear priorities, healthy team rhythms, and focus on meaningful work
• Align priorities and investments with Product, Security Research, AI, Infrastructure, and Customer teams
• Communicate platform strategy, progress, risks, and trade-offs clearly to executive leadership
• Partner with customer-facing teams to anticipate evolving data requirements and scaling challenges
• Influence company-wide direction on data, AI, and platform capabilities
• Lead delivery of large-scale platform initiatives, balancing innovation, reliability, and speed
• Define and enforce engineering best practices across data processing, schema evolution, data quality, and service-level objectives
• Own production operations, incident management, and continuous improvement
• Ensure predictable delivery while maintaining focus on customer impact and long-term platform health
• Engage deeply on architecture for scalable, reliable, AI-ready infrastructure and pressure-test designs with platform architects
• Champion a platform-first mindset with self-service APIs, robust developer tooling, observability, and clear documentation
• Drive adoption of modern capabilities including feature stores, vector storage, and model serving infrastructure
• Champion the use of AI to improve engineering productivity, software delivery, and incident response

Job Requirements:

• 10+ years of software engineering experience, including 5+ years leading engineering organizations
• Proven track record building and operating large-scale data platforms in production
• Deep expertise in large-scale data infrastructure: distributed systems, ingestion pipelines, stream and batch processing, and storage at scale (object stores, columnar databases, time-series systems)
• Hands-on experience with Databricks, Spark-based processing, and the Databricks platform ecosystem
• Experience running ML or AI workloads in production, including platforms, feature stores, and inference infrastructure
• Operational mindset with strong grounding in SRE principles, incident response, and reliability practices
• Experience building or operating platforms that support LLM-based applications, including retrieval, embeddings, and model serving
• Demonstrated ability to champion and apply AI to improve engineering productivity, software delivery, and incident response
• Preferred: Background in cybersecurity, NDR, SIEM, XDR, observability, or related domains
• Preferred: Proven ability to optimize cloud costs and performance at scale on AWS, Azure, or GCP
• Preferred: Experience with real-time detection systems or streaming analytics.