Director, Engineering - Data Infrastructure & Reliability

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn't changed — we're here to stop breaches, and we've redefined modern security with the world's most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We're proud to work for a mission-driven company leveraging AI to transform the way we work. CrowdStrikers drive their careers through flexibility and autonomy while also being expected to contribute to a culture of responsible AI adoption, experimentation, and innovation. We use an AI-first mindset as a force multiplier to proactively and continuously accelerate execution, build expertise, uncover insights, and solve complex problems. We're always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. The future of cybersecurity starts with you. CrowdStrike's Data Platform is the foundation beneath Falcon and Next-Gen SIEM: the ingestion, streaming, storage, and query systems that take in almost 3 trillion events per day, at millions of events per second, and make them searchable in seconds. It spans multiple clouds and regions, including sovereign and regulated environments, and it holds petabytes of security telemetry that customers rely on in the middle of active investigations.

We set a high bar for that platform. Reliability, cost efficiency, and provable compliance are engineering requirements here rather than afterthoughts, and we are raising that bar again as we move the organization toward domain ownership, data as a product, self-serve tooling, and federated governance.

We support planetary scale and our systems are stateful and order-dependent, which puts them outside what generic cloud build automation is designed for. Validating a change means tracing real data from the sensor through ingestion to query rather than exercising a service in isolation. The largest cost levers are spread across every team that queries or stores data. We are forming a centralized Data Platform Enablement team to own that category of work, and we are hiring its founding engineering leader.

It builds platform-wide automation, tooling, and test infrastructure. It partners hands-on with individual data platform teams. Every hour your team spends on cross-cutting reliability, testing, and cost work is an hour another data platform team gets back for work in its own domain.

Organizational Leadership & Team Building Stand up the team: define its operating model, hire net-new engineers, and bring in senior operators from existing data platform teams without leaving holes behind them. Hire, develop, and lead engineering managers and technical leads as the team grows from one group into several domain-aligned ones. Own org design as the charter matures: forming, rechartering, and sequencing teams against where the platform's risk actually sits.

Cloud Expansion Automation Build the automation that makes stateful data platform systems first-class citizens in our cloud build tooling, including the ordering, state awareness, and dependency sequencing that generic SRE automation cannot handle. Take regional and sovereign cloud build-outs to full automation, so standing up a new environment is a repeatable, hands-off sequence. Own time-to-launch per cloud and region as a headline metric, alongside the teams that own the destination architecture.

Build a testing system that generates and traces data from the CrowdStrike sensor through ingestion to query validation. The same harness does pre-launch validation for every new cloud and region, then continuous health checks in steady state. Raise the fidelity of generated test data so it exercises the same paths production traffic takes, and a passing run means what it claims. Standardize reliability and efficiency metrics across every data platform team, so the whole platform reports from one instrumented view. Build detection that catches problems before customers report them, with automated routing to the right responders plus first-line triage and guidance for owning teams. Push the incident rate between releases and operations down by addressing systemic causes.

Cost Engineering Some of it is pipeline and architecture rework. Move cost accountability to the layers that own the levers, so that application teams see what their query patterns, storage choices, and pipeline hops actually cost. This is as much an organizational change as a technical one, and you will lead it.

Resilience, Scale & Capacity Planning Establish a recurring game day practice that stresses systems deliberately to establish their real limits. Run scale and stress testing ahead of projected demand. Work with data platform teams on forward-looking capacity planning, and hold forecast accuracy as a real metric.

Data Residency & Compliance Automation Turn residency verification and audit evidence into reusable platform capabilities that every new region inherits. your team automates the data platform's side of proving both. Build automated validation that data lands, is processed, and is queried inside its declared residency boundary, wired into the same harness as the rest of the testing rather than a parallel one. Express the data platform's share of sovereign and certification controls as executable checks that run continuously, and generate attestation evidence from telemetry so certification and re-certification draw on evidence that is always current. Turn your team's delivery into a clear executive story on reliability, cost, and compliance posture, and carry it into senior forums with candor about risk. Earn adoption from engineering leaders who do not report to you. 12+ years of software engineering experience, including 5+ years leading engineering teams and at least 2 years leading through other managers.

A track record of building, growing, and retaining high-performing platform, SRE, or infrastructure teams in a fast-paced, high-growth environment, including hiring senior engineers onto a team that did not exist yet.

SLOs, SLIs, error budgets, incident command, blameless postmortems, and capacity planning for high-throughput distributed systems.

Experience owning reliability for large-scale stateful distributed systems, where ordering, data state, and recovery semantics rule out generic automation. Working fluency with distributed data infrastructure: streaming platforms, OLAP and search engines, object storage, and large-scale query systems. Ownership of a substantial infrastructure cost portfolio, including driving optimization across organizational boundaries and shifting cost accountability to the teams that control the spend.

You have changed how engineering teams outside your reporting line operate, and you can explain how you earned that adoption instead of mandating it.

Experience operating under regulatory, residency, or certification constraints, and comfort turning control requirements into engineering work.

A specific point of view on applying AI to reliability and operations: where it pays off, where it does not, and what you would build first.

Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes.

Bachelor's degree in Computer Science or related field, or equivalent work experience.

Bonus Points: Experience standing up sovereign, air-gapped, or regulated cloud environments, and automating the evidence that proves they comply. Python and/or Golang, Infrastructure as Code (Terraform, Ansible, Pulumi), Kubernetes at fleet scale, and GitOps workflows. Having built and run a chaos engineering or game day practice that other teams joined voluntarily. Having shipped LLM-native or agentic tooling for incident prevention, triage, or remediation.

This role will require the candidate to periodically undergo and pass additional background and fingerprint check(s) consistent with government customer requirements.

Market leader in compensation and equity awards Competitive vacation and holidays for recharge Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections Vibrant office culture with world class amenities We support veterans and individuals with disabilities through our affirmative action program.

The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements.

If you need assistance accessing or reviewing the information on this website or need help submitting an application for employment or requesting an accommodation, please contact us at participates in the E-Verify program.

CrowdStrike, Inc. is committed to fair and equitable compensation practices. Placement within the pay range is dependent on a variety of factors including, but not limited to, relevant work experience, skills, certifications, job level, supervisory status, and location. S. candidates is $195,000 - $290,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off.