Senior Software Development Engineer

F5 F5 · Enterprise · Seattle, WA +1

Senior Software Engineer for F5's Infrastructure Engineering Data Team, focused on building enterprise applications and data-driven solutions. The role involves leading the design and development of an enhanced telemetry pipeline, improving performance and operational excellence, and setting technical direction for scalable data pipeline systems. The engineer will also mentor team members and drive quality improvements through automated testing and CI/CD gates. Experience with ML models and AI techniques for decision making is required.

What you'd actually do

  1. Set technical direction for scalable and secure data pipeline systems, defining what “good” looks like and championing best practices and design patterns.
  2. Build collaboration across teams and functions to drive alignment on outcomes and unblock systemic issues that slow delivery or reduce quality.
  3. Own software components end-to-end, raising standards for functional excellence, scale, performance, security and operability, and leaving systems measurably better than you found.
  4. Multiply team impact through technical leadership and mentoring, uplifting engineering judgement, design quality, and execution habits.
  5. Recommend, establish and maintain technical design methodologies and processes to raise quality and reduce risk, challenging the status quo when needed.

Skills

Required

  • Golang
  • Java
  • Python
  • Scala
  • C++
  • SQL
  • NoSQL
  • Flink
  • Spark
  • EMR
  • Docker
  • Kubernetes
  • AWS
  • GCP
  • Machine Learning models
  • AI techniques

Nice to have

  • PromQL
  • Tableau
  • Grafana

What the JD emphasized

  • Expertise with any combination of programming languages: Golang, Java, Python, Scala, C++ or any high-level proprietary or open-source language with strong programming constructs.
  • Expertise in building and operating high-scale data pipelines
  • Strong background with SQL or NoSQL databases and performance tuning.
  • Strong experience with distributed compute technologies, such as Flink, Spark, EMR
  • Hands on experience with Docker and Kubernetes as well as developing applications using microservices architecture with Cloud platforms such as AWS or GCP.
  • Implementation experience with Machine Learning models and AI techniques for improved decision making.