Are you prepared to launch a cloud-based career?
Cloud Data Engineers are at the vanguard of the global digital transformation of enterprises, influencing the handling, storing, and use of data.
Google, a pioneer in this digital transformation, is hiring bright people in Pune, Bengaluru, and Hyderabad to fill the position of Cloud Data Engineer.
This position is essential to assisting businesses in using cloud computing to boost productivity and innovation.
About Cloud Data Engineer at Google
A collection of cloud computing services called Google Cloud Platform (GCP) are powered by the same internal infrastructure that Google utilizes for its consumer products, including YouTube, Gmail, and Google Search.
In a world where digitalization is king, GCP provides dependable and scalable cloud solutions to help businesses remain competitive.
GCP offers the resources needed to create, launch, and grow apps with ease, regardless of the application—big data, machine learning, or IoT.
Locations for This Role
In three thriving tech hotspots in India, Google is seeking Cloud Data Engineers:
- Pune, Maharashtra: Dubbed the “Oxford of the East,” Pune is a burgeoning IT centre that combines elements of the modern and traditional worlds.
- Karnataka’s Bengaluru: Known as the “Silicon Valley of India,” Bengaluru is the nation’s center for creativity and technology.
- Hyderabad, Telangana: Hyderabad is fast becoming as a key participant in the IT and cloud computing market because to its thriving tech sector
Minimum Qualifications
- Educational Requirements: A bachelor’s degree in computer science, engineering, mathematics, or a similar discipline is required for admission. Similar real-world experience is also permitted.
- Programming Skills: This position requires proficiency in at least one programming language, such as Python, Java, or Scala.
- Experience with Client-Side Web Technologies: It need knowledge of web technologies like HTML, CSS, and JavaScript to be able to comprehend and work with various web application components.
- Technical Troubleshooting Skills: Expertise in identifying and resolving technical problems, as well as successful management of partners or customers, both internal and external.
Apply Here: Cloud Data Engineer at Google
- Job Designation: Cloud Data Engineer
- Salary: 15 – 25 LPA
- Qualification: B-Tech
- Experience: 0 – 2 Years
- Organization Name: Google Cloud
- Website: Google Cloud
- Industry: IT Technology
- Locations: Pune, Bengaluru, and Hyderabad
- Mode: Hybrid
Preferred Qualifications
The following recommended qualifications can give you an advantage, even though the minimum requirements are still quite important:
- Experience with Big Data Solutions: Proven track record in designing and implementing enterprise-class big data solutions in virtualized settings.
- Understanding of CI/CD Tools and IaC: knowledge of Continuous Integration/Continuous Deployment (CI/CD) and Infrastructure as Code (IaC) tools such as Terraform, Ansible, and Jenkins.
- Proficiency in Data Warehousing and Tools for Analysis: familiarity with cloud-based data warehouses, ETL/ELT procedures, and reporting and analytical tools.
- Expertise in Contemporary Data Processing Techniques: familiarity with big data technology, machine learning principles, and data processing frameworks.
- Acquaintance with Contemporary Technologies and Multi-Tier Applications: familiarity with using data processing tools like SparkML and NoSQL databases like MongoDB for the development and upkeep of apps.
Job Responsibilities: Cloud Data Engineer at Google
The following broad range of duties are essential to the position of Google Cloud Data Engineer:
- Taking in, Storing, and Processing Data: Assist clients in effectively taking in, storing, processing, and displaying data on GCP.
- Creating Large-Scale Data Processing Systems: Collaborate with clients to create scalable, high-performing data processing systems.
- Projects involving data migration and modernization: Oversee the modernization and migration of the data infrastructure to guarantee seamless transitions and improved capabilities.
- Providing Data Security and Governance: To safeguard data integrity and compliance, put in place strong data governance and security measures.
Interacting with Stakeholders
- Recognizing Customer Needs: Communicate with customers to comprehend their intricate needs and convert them into recommendations that may be put into practice.
- Converting Specifications into Architectures for Solutions: Create solution architectures and offer consulting services that satisfy the requirements and demands of clients.
Engaging with Technical Leads and Partners
- In charge of Modernization and Migration: Drive high-velocity migration and modernization initiatives to GCP in collaboration with technical leads.
- Working Together on High-Speed Projects: Assist other teams and partners closely to guarantee project delivery success and client satisfaction.
Design and Implementation
- Creating Infrastructure for Data Processing and Storage: Using cloud-native products, design and implement reliable systems for data processing and storage.
- Putting Data Migration Strategies into Practice: Create and carry out plans to move different kinds of databases—like PostgreSQL and Oracle—to the cloud.
Developing Data Quality and Governance Procedures
Assuring Data Accuracy and Reliability: Create policies and processes to uphold data governance and quality, guaranteeing data accuracy and consistency across systems.
Why Work at Google Cloud?
For Cloud Data Engineers, Google Cloud provides a stimulating and fulfilling environment:
- Benefits of Joining Google’s Team: Take advantage of a dynamic workplace that promotes diversity, creativity, and professional development.
- Google’s dedication to excellence and innovation: Become a member of an organization that sets the standard for technology innovation and digital transformation.
Skills and Tools You’ll Use
- Programming Languages: To design and manage cloud systems, proficiency with Python, Java, and Scala is essential.
- Tools: You’ll work with data technologies like NoSQL, MongoDB, and SparkML as well as state-of-the-art tools like Terraform, Ansible, and Jenkins.
The Application Process:
What you need know about the application procedure is as follows:
Online Application: Fill out the application on Google’s careers page and submit your resume.
First Screening: A recruiter will contact you for a phone interview if your application meets the requirements for the position.
Technical Interviews: Be ready for several rounds of interviews that will concentrate on your problem-solving, cloud-computing, and coding expertise.
Onsite Interviews: Should you clear the technical rounds, you’ll be invited to participate in virtual or onsite interviews that entail in-depth behavioral and technical evaluations.
Conclusion:
Being at the forefront of technical innovation is an amazing opportunity that comes with joining Google as a Cloud Data Engineer.
You’ll collaborate with cutting-edge technology, be a member of an energetic team, and influence how companies operate globally.
Frequently Asked Questions (FAQs)
1. What is the role of a Google Cloud Data Engineer?
On the Google Cloud Platform (GCP), a Cloud Data Engineer at Google creates and oversees scalable data solutions. They assist customers with database migration, data ingest, storage, processing, and visualization, as well as data security and quality assurance.
2. What credentials are needed to apply to Google for the post of Cloud Data Engineer?
A bachelor’s degree in computer science, engineering, mathematics, or a similar discipline is required of candidates, as well as equivalent real-world experience.
3. What kinds of projects will I be involved in as a Google Cloud Data Engineer?
In addition to developing large-scale data processing systems, putting data governance and security measures in place, and working with clients to convert their needs into practical data solutions on GCP, you will be working on projects including data migrations and modernization.
4.What qualifications can make me stand out if I apply for this job?
Big data solutions experience, familiarity with NoSQL databases, machine learning, and data processing frameworks, as well as knowledge of Infrastructure as Code (IaC) and Continuous Integration/Continuous Deployment (CI/CD) tools like Terraform and Jenkins, can all help you stand out as a strong candidate.
