Vacancy expired!
- Passionate about data infrastructure and deep engineering background
- Proven track record of development and administration in Linux environment
- Experience deploying and managing distributed systems for big data processing/streaming/storage engines (e.g., Apache HDFS, Apache Spark, Apache Impala, Parquet) along with resource management systems (e.g., Apache Mesos, Kubernetes)
- PySpark and Java experience is a must.
- Experience integrating and deploying analytics frameworks (e.g. Jupyter notebooks, Apache Livy) for big data processing
- Experience with alerting, monitoring, and remediation automation in a large scale distributed environment
- Extensive programming experience in Java or Python
- Interest or knowledge in using public or private Kubernetes frameworks for scaling data and services infrastructure
- Responsible for the Data Infrastructure used for analytics and machine learning of the Device Intelligence & Analytics (DIA) team. DIA infrastructure stores, processes, and serves 100s of TeraBytes of data for millions of users. The DIA team’s goal is to ensure reliability and performance at the highest level.
- Manage DIAs data infrastructure to support analytical capabilities, tooling, and workloads.
- Take part in designing and building out our next-generation research environment to push our on-premise data services to the next level
- Diagnose, fix, improve, and automate complex issues across the entire stack to ensure maximum uptime and performance
- Collaborate across the DIA team on proper use/integration of our platform
- Provide guidance and indoctrination on established industry best practices to maximize the performance of our platform’s analytical capabilities
- Write code, documentation, participate in code reviews, and mentor other engineers
- Bachelor's or Master’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.
Vacancy expired!