Google Cloud Platform Data Architect

Overview

On Site
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 12 Month(s)
100% Travel
Able to Provide Sponsorship

Skills

GCP
Natural Language Processing
Python
Data Bricks

Job Details

Experience:

  • 10+ years of relevant Total IT work experience
  • 5+ years of experience in Data Engineer
  • 2+ years of experience in Principal Data Engineer/Architect

 

Required

A successful candidate will have:

  • Strong understanding of best practices and standards for Google Cloud Platform application design and implementation.
  • Two+ Year of hands-on experience with Google Cloud Platform platform and experience with many of the following components:
    • GCS, Cloud Run, Cloud Functions
    • Bigtable, Cloud SQL
    • Kafka, Pub/Sub
    • Python, Golang, Spark, Scala or Java
    • BigQuery, Dataflow, Data Fusion
    • GKE, CI/CD and Logging & Monitoring
  • Understanding of Lambda Design Architectures and Real-Time Streaming
  • Experience with Unstructured Data, Real-Time Streaming with Google Cloud Platform
  • Ability to multitask and to balance competing priorities.
  • Requires strong practical experience in agile application development, file systems management, and DevOps discipline and practice using short-cycle iterations to deliver continuous business value.
  • Knowledge of all facets of Google Cloud Platform ecosystem development including ideation, design, implementation, tuning, and operational support.
  • Ability to define and utilize best practice techniques and to impose order in a fast-changing environment. Must have strong critical thinking skills.
  • Strong verbal, written, and interpersonal skills, including a desire to work within a highly matrixed, collaborative environment.
  • A successful candidate may have:
    • Experience in Healthcare Domain
    • Experience in Patient Data
    • Experience with Natural Language Processing (NLP)

 

Hardware/Operating Systems:

  • Linux, UNIX
  • Google Cloud Platform
  • Distributed, highly scalable processing environments.

 

Databases:

  • RDBMS MS SQL Server/Teradata/Oracle
  • NoSQL, HBase, Cassandra, MongoDB, In-memory, Columnar, other emerging technologies
  • Build Systems TFS, Maven, Ant
  • Source Control Systems Git, Mercurial
  • Continuous Integration Systems Jenkins or Bamboo

 

Certifications (a plus, but not required):

  • Google Cloud Platform Cloud Professional Data Engineer
  • Google Cloud Platform Cloud Professional Data Architect

 

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