Google Recruitment 2020 for Data Engineer at Bangalore. Please read the entire information carefully and apply if you are eligible.
Eligibility Criteria for Data Engineer at Google:
- Education: B.E / B.Tech / M.E / M.Tech (CSE, ECE, IT) / MCA
- Skills: Python, Spark, Big Data, Hadoop
- Last date: ASAP
- Job Location: Bangalore
- Experience: 3 years
- Job Code: Google Data Engineer Job Opening
Key skills required at for Data Engineer at Google:
- Bachelor’s degree in Computer Science or related technical field, or equivalent practical experience.
- 3 years of industry experience in software development, data engineering, business intelligence, data science, or related field with experience in manipulating, processing, and extracting value from datasets.
Preferred qualifications for Google Hiring For Data Engineer Position:
- Master’s degree in Computer Science, or related field.
- Understanding of Big Data technologies and solutions (Spark, Hadoop, Hive, MapReduce) and multiple scripting and languages (YAML, Python).
- Understanding of Google Cloud Platform (GCP) technologies in the big data and data warehousing space (BigQuery, Cloud Data Fusion, Dataproc, Dataflow, Data Catalog).
- Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
- Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences.
Responsibilities for Google Hiring For Data Engineer Position
- Design, build and deploy internal applications to support our technology life cycle, collaboration and spaces, service delivery management, data and business intelligence among others.
- Work closely with analysts and business process owners to translate business requirements into technical solutions.
- Build internal solutions, with custom front ends (web, mobile) and backend services that automate business processes.
- Maintain highest levels of development practices including: technical design, solution development, systems configuration, test documentation/execution, issue identification and resolution, writing clean, modular and self-sustaining code, with repeatable quality and predictability.
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