AI/ML – Data Infrastructure Engineering Manager, Client Engineering and Tooling, Siri Search & Knowledge Platform


Job Overview

Key Qualifications

  • – 8+ years of experience in big data ecosystem. Example technologies include batch and stream processing (e.g. Spark, Hive, Flink, Beam), analytical engines (e.g. Presto, Druid), search platform (e.g. Solr/Lucene), tooling (e.g. Airflow, Jupyter, Superset, Tableau), and storage format (e.g. Iceberg)
  • – 2+ years of experience building and leading a team of highly-skilled software engineers
  • – Excellent verbal and written communication skills, able to collaborate cross-functionally with data science, machine learning, data platform and analytics teams
  • – Superb problem-solving skills, and able to thrive in a fast-paced and dynamic environment
  • – Prior hands-on experience in designing, building, and scaling solutions to big data problems
  • – Must have strong project management skills, scrum master experience is a big plus
  • – Programming experience in Java, Python, Scala, or similar languages
  • – Passionate about latest big data technologies, open source community presence is a big plus
  • – Experience with AWS, Kubernetes, Infrastructure-as-code, and data privacy & compliance is a big plus
  • Description

    You will be responsible for managing a client-facing team that drives user engagement with our new generation of data platform, collaborates cross-functionally with data, product management, and infrastructure teams, and provides tooling support to enable ingesting, storing, processing and interacting of data with a focus in user experience. RESPONSIBILITIES INCLUDE:- Manage, mentor, and grow a team of engineers who operate our data tooling infrastructure – Collaborate with our infrastructure users and product management to ensure success in customer engagement and onboarding of new users – Be an advocate of our tech stack, stay on top of technology advancement and explore innovation opportunities – Foster a healthy, collaborative, and technology-driven culture, and a high output team – Expected 50% time on technical work, including prototyping, problem solving with team, technology evaluation, performance tuning, architecture and code reviews, etc. – Drive technical and cross-functional projects and provide leadership in an innovative and fast-paced environment – Measure and improve the reliability and scalability of data infrastructure systems

    Education & Experience

    BS, MS, or PhD degree in Computer Science or equivalent

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