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GCP Data Engineer

Added 4 days ago

GCP Data Engineer| 5-8 Yrs| WFO - PradeepIT Consulting Services Pvt Ltd | Career Page

GCP Data Engineer| 5-8 Yrs| WFO

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Job Openings GCP Data Engineer| 5-8 Yrs| WFO

About the job GCP Data Engineer| 5-8 Yrs| WFO

Role GCP Data Engineer

Experience:5~8 years

Preferred - Data Engineering Background

Location - Chennai, Pune, Kolkata, Hyderabad

Immediate joiners only

Required Skills - GCP DE Experience, Big query, SQL, Cloud compressor/Python, Cloud functions, Dataproc+pyspark, Python injection, Dataflow+PUB/SUB

# of roles - 2

Work Mode- C2H (after 8 months)

Here is the job description for the same -

Job Requirement:

  • Have Implemented and Architected solutions on Google Cloud Platform using the components of GCP

  • Experience with Apache Beam/Google Dataflow/Apache Spark in creating end to end data pipelines.

  • Experience in some of the following: Python, Hadoop, Spark, SQL, Big Query, Big Table Cloud Storage, Datastore, Spanner, Cloud SQL, Machine Learning.

  • Experience programming in Java, Python, etc.

  • Expertise in at least two of these technologies: Relational Databases, Analytical Databases, NoSQL databases.

  • Certified in Google Professional Data Engineer/ Solution Architect is a major Advantage

Skills Required:

  • 5~8 years experience in IT or professional services experience in IT delivery or large-scale IT analytics projects

  • Candidates must have expertise knowledge of Google Cloud Platform; the other cloud platforms are nice to have.

  • Expert knowledge in SQL development.

  • Expertise in building data integration and preparation tools using cloud technologies (like Snaplogic, Google Dataflow, Cloud Dataprep, Python, etc).

  • Experience with Apache Beam/Google Dataflow/Apache Spark in creating end to end data pipelines.

  • Experience in some of the following: Python, Hadoop, Spark, SQL, Big Query, Big Table Cloud Storage, Datastore, Spanner, Cloud SQL, Machine Learning.

  • Experience programming in Java, Python, etc.

  • Identify downstream implications of data loads/migration (e.g., data quality, regulatory, etc.)

  • Implement data pipelines to automate the ingestion, transformation, and augmentation of data sources, and provide best practices for pipeline operations.

  • Capability to work in a rapidly changing business environment and to enable simplified user access to massive data by building scalable data solutions

  • Advanced SQL writing and experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with complex datasets

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