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    Cloud Big Data Applications Support - Montreal, Canada - TELUS

    TELUS
    TELUS Montreal, Canada

    4 weeks ago

    Telus background
    Full time
    Description

    Description

    Be a part of a transformational journey with innovative talent and leading edge technologies.

    Join our team

    Google Cloud technology is an industry leader in empowering millions of organizations and businesses to lead, innovate and grow. If you are interested in working with this leading edge technology while providing best in class technical customer support, consider this great opportunity at TELUS.

    Here's the impact you'll make and what we'll accomplish together

    As a Big Data Applications Support Specialist within the TELUS Google Cloud team, your role will be to provide excellent technical customer service support for Google Cloud Platform products and solutions including Big Data related applications. Working in a blended call center environment, you will provide real time technical assistance over the phone and via online communications based on client requirements as part of a global 24x7 support organization. This role will also work closely with engineers and product managers to improve the product and make our customers successful.

    Here's How

  • Provide technical and developer support to customers using Google Cloud Platform products, solutions and APIs
  • Identify and document both product bugs and feature requests, and continually working with internal support teams as well as customers to implement effective solutions
  • Reproduce customer issues in order to better understand their use cases, and to efficiently provide tailored solutions for their environments.
  • Work closely with various internal support teams to progress case-related work and to also improve Google Cloud Platform products at both a granular and higher level

    • Qualifications

    You're the missing piece of the puzzle

    Must have:

  • Firm understanding of a programming language (Java Python preferred)
  • Demonstrate comprehensive and logical troubleshooting methodologies
  • Ability to quickly learn, explain, and put intopractice newly complex technologies and subjects
  • Resourcefulness and strong research skills
  • Significant abilities in reading, understanding and writing code samples to replicate customer issues, as well as reading and understanding logs and stack traces
  • Must be proficient Orally and Written in both English and French, as well as professional communication skills
  • Strong understanding of various Networking Protocol Stacks (TCP, IP, HTTP(S), etc.)
  • Familiarity with modern API technologies (OAuth, HTTP RPCs, REST, HTTP response codes)
  • Comfortable with terms and concepts used within Computer Science (API, schema, pipelines, system workflows, databases, natural language processing, etc.)
  • Punctuality, aware of professional etiquette standards, and 24/7 availability

    • Additional Skills

    Great-to-have

  • Firm understanding of emerging AI & ML technologies (especially for model analysis, training, and tuning)
  • Experience with PaaS, SaaS, and IaaS technologies
  • Experience in technical support: familiarity with case prioritization, SLA compliance, and able to provide high levels of customer-focused quality
  • Experience in deploying and managing distributed systems and clusters (Kubernetes), workflows, and familiarity with testing environments
  • Knowledge of SQL (any dialect), running and interacting with various types of queries, and familiarity with Tensorflow
  • Customer Service Experience

    • Preferred Qualifications:

  • College diploma in Computer Science or 2 years equivalent knowledge / experience
  • Firm understanding of specific programming languages: Java, Python, , Go
  • Experience with distributed data stores (HBase, Cassandra, Riak, Amazon Dynamo DB, etc.) and distributed message brokers (Kafka, RabbitMQ, ActiveMQ, Google Pub/Sub, Amazon Kinesis, etc.)
  • Familiarity with parallel/distributed computing (Apache Beam, MapReduce, Hadoop, Spark, Google Dataflow, Google Dataproc, etc.)
  • Experience with Big Data architectures and technologies (Google Data Fusion, CDAP, Google Dataprep, Trifacta, Google BigQuery, Google Composer, Apache Airflow, etc.)
  • Experience with any ML library (scikit-learn, pytorch, tensorflow, Spark mllib) or basic understanding of training, testing, and evaluating ML models
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