Data Engineer _GCP Build | 9-12 years | Pan India

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Capgemini

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Job Summary


Salary
โ‚น41,136 - โ‚น79,318 / Monthly EST

Job Type
-

Seniority
Mid

Years of Experience
Information not provided

Tech Stacks
BigQuery Spark SQL Hadoop

Job Description

Job Description

  • You will be responsible for designing building and maintaining our data infrastructure ensuring data quality and enabling data driven decision making across the organization.
  • The ideal candidate will have a strong background in data engineering excellent problem solving skills and a passion for working with data Responsibilities.
  • Design build and maintain our data infrastructure including data pipelines warehouses and databases.
  • Ensure data quality and integrity by implementing data validation testing and monitoring processes Collaborate with cross functional teams to understand data needs and translate them into technical requirements.
  • Develop and implement data security and privacy policies and procedures Optimize data processing and storage performance ensuring scalability and reliability Stay up to date with the latest data engineering trends and technologies.
  • Provide mentorship and guidance to junior data engineers and analysts Contribute to the development of data driven solutions and products.
  • Requirements 3 years of experience in data engineering with a Bachelor s degree in Computer Science Engineering or a related field Strong knowledge of data engineering tools and technologies including SQL and GCP Experience with big data processing frameworks such as Spark or Hadoop Experience with data warehousing solutions BigQuery Strong problem solving skills with the ability to analyze complex data sets and identify trends and insights.
  • Excellent communication and collaboration skills with the ability to work with cross functional teams and stakeholders Strong data security and privacy knowledge and experience Experience with agile development methodology.

Primary Skills

  • Data Engineer
  • GCP Cloud

Secondary Skills

  • BigQuery
  • Spark or Hadoop

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