Sr. Manager, Engineering - Data Analytics Infrastructure (Hybrid)

CrowdStrike · USA - Austin, TX · USA - New York, NY

onsitefull-time6-10 years

posted 19 Aug

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. Ready to join a mission that matters? The future of cybersecurity starts with you. About the Role: CrowdStrike is seeking a Sr Engineering Manager (L8) to lead a host of initiatives spanning 2-3 teams with coverage in MLOps & broader data infrastructure, as well as data analytics platform & data recovery initiatives. Your teams would own data plane infrastructure that runs a multitude of Spark-, Flink- and other apache-based applications at incredibly high scale (over 3 Trillion events/day) both in our cloud environments as well as data centers. You own the setup, deployment, scaling and management of all data plane products that are used to ingest, process and enrich event stream data that are part of the Falcon platform. In addition, you will continue to build out & scale teams capable of supporting the myriads of services running within the our data infrastructure. You will work closely with engineers and product to understand requirements and cross functionally with peers and senior leadership to deliver innovative products that can scale with increased demand. CrowdStrike is a remote-first organization and this position requires the ability to hold meetings with team members across US and EU time zones. This is a Hybrid role requiring an 2 days per week in one of our office Locations (Austin, TX or Mid-town Manhattan, NY) What You'll Do: Lead multiple teams in the design, scaling and maintenance of data infrastructure services operating at 100s of PBs scale Train, mentor and continue to hire top-tier data platform engineering talent What You'll Need: MS in Computer Science or related field 10+ years of software engineering experience in building and/or managing large scale data platforms 5+ years of hands-on management experience leading distributed engineering teams Experience building and supporting real time or NRT data systems of ultra high scale (MINIMUM: 100s of TB/day in either a current or past role) Significant expertise in performance-tuning or developing internals (source code) within Spark, Flink, Iceberg or Pinot or an equivalent structured streaming, Time Series, OLAP or Open Table real time system. Production experience building either Spark- or Flink-based self-service data platforms, or equivalent (i.e. with Ray, or building spark- or Flink-like frameworks themselves in Scala, Akk, etc.) Strong familiarity with (and ample hands-on experience tuning & optimizing) at least one applicable technology in the Apache Hadoop ecosystem: Spark, Kafka, Hive/Iceberg/Delta Lake, Presto/Trino, Pinot, Druid, etc. Ample e xperience coding in Java, Scala, Kotlin or another JVM language (bonus points for experience tuning the language, i.e. garbage collection, memory management…) Production experience with relational SQL and NoSQL data