Director of Engineering (Data Platform)

Vectra•Austin, TX

2h•$189,000 - $222,300

About The Position

Vectra is seeking a Director of Engineering to lead the teams responsible for the foundational data platform. This platform ingests, processes, stores, and analyzes petabytes of security telemetry daily, supporting modern AI workloads, autonomous security workflows, and next-generation analytics. The role requires strong organizational leadership with non-negotiable technical credibility, including architectural fluency and the ability to engage deeply in system design. The Director will work closely with platform architects, drive technical direction, and ensure the platform's evolution to meet the demands of AI and advanced analytics in cybersecurity.

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 across large-scale data infrastructure: distributed systems, data ingestion pipelines, stream and batch processing, and storage systems at scale including object stores, columnar databases, and time-series systems.
Experience with Databricks, including Spark-based processing and the Databricks platform ecosystem.
Experience running ML or AI workloads in production, including platforms, feature stores, or inference infrastructure.
Operational mindset: SRE principles, incident response, and a culture of reliability.
Experience building or operating platforms that support LLM-based applications, including retrieval, embeddings, and model serving.

Nice To Haves

Background in cybersecurity, NDR, SIEM, XDR, observability, or related domains.
Track record optimizing cloud costs and performance at scale on AWS, Azure, or GCP.
Background in real-time detection systems or streaming analytics.

Responsibilities

Build, grow, and mentor high-performing engineering teams across multiple geographies.
Develop engineering managers and senior technical leaders through coaching, sponsorship, and career investment.
Foster an inclusive culture built on trust, ownership, and accountability, where distributed teams can do their best work.
Create the conditions for strong execution: clear priorities, healthy team rhythms, and an environment where engineers can focus on meaningful work.
Align priorities and investment decisions 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 understand evolving data requirements and scaling challenges.
Influence company-wide direction around data, AI, and platform capabilities.
Lead delivery of large-scale platform initiatives, balancing innovation, reliability, and speed.
Set 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 keeping a clear line of sight to customer impact and long-term platform health.
Engage deeply on architecture decisions for scalable, reliable, and AI-ready infrastructure, able to ask hard questions, identify gaps, and pressure-test designs alongside platform architects.
Champion a platform-first mindset with self-service APIs, strong developer tooling, observability, and documentation that accelerate Data Science, AI/ML, and product teams.
Drive adoption of modern platform capabilities including feature stores, vector storage, and model serving infrastructure.
Champion the use of AI to improve engineering productivity, software delivery, and incident response.