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

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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