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Job Closed

Cloud Data Engineer

  • Source: LinkedIn
  • Google
  • On-site
  • Hyderabad
  • Full-Time
  • Mid level

Job Description

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Bengaluru, Karnataka, India; Hyderabad, Telangana, India . Minimum qualifications:

  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
  • 3 years of experience in developing and troubleshooting data processing algorithms and softwares using Python, Java, Scala, Spark and hadoop frameworks.
  • Experience working with one or more public cloud providers (e.g., Google Cloud Platform).
  • Ability to travel up to 30% as required.

Preferred qualifications:

  • Experience in working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT and reporting/analytic tools, environments, and data structures.
  • Experience in Big Data, information retrieval, data mining, or machine learning.
  • Experience in building multi-tier, high availability applications with modern technologies such as NoSQL, MongoDB and SparkML.
  • Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.
  • Experience with IaC and CICD tools like Terraform, Ansible, Jenkins etc.

About The Job As a Cloud Data Engineer, you will guide customers on how to ingest, store, process, analyze, and explore/visualize data on the Google Cloud Platform. You will work on data migrations and modernization projects, and with customers to design data processing systems, develop data pipelines optimized for scaling, and troubleshoot potential platform/product challenges. You will have knowledge of data governance and security controls. You will travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you’ll work closely with Product Management and Product Engineering teams to build and constantly drive excellence in our products.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

  • Interact with stakeholders to translate complex customer requirements into recommendations for appropriate solution architectures and advisory services.
  • Engage with technical leads, and partners to lead high velocity migration and modernization to GCP. Design, migrate/build, and operationalize data storage and processing infrastructure using cloud native products.
  • Design and implement data migration strategies for various database types (e.g., PostgreSQL, Oracle, Alloy DB, etc.).
  • Develop and implement data quality and governance procedures to ensure the accuracy and reliability of data. Create communication strategies, risk and issue management, status reports, project matrix, and track timelines.
  • Take various project requirements and organize them into clear goals and objectives, and create a work breakdown structure to manage internal and external stakeholders.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .

Skills

  • Python
  • Java
  • Scala
  • Spark
  • Hadoop
  • apache-hadoop
  • MongoDB
  • Terraform
  • Ansible
  • Jenkins
  • google-cloud-platform
  • PostgreSQL
  • oracle
  • alloy
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