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Tredence Analytics Solutions - GCP Data Engineer - Python/BigQuery
Tredence Analytics Solutions - GCP Data Engineer - Python/BigQueryTredence INC. • Kolkata
Tredence Analytics Solutions - GCP Data Engineer - Python / BigQuery

Tredence Analytics Solutions - GCP Data Engineer - Python / BigQuery

Tredence INC. • Kolkata
5 days ago
Job description

Description :

Role : GCP Data Engineer

Experience : 5+ years

Preferred : Data Engineering Background

Location : Bangalore, Chennai, Pune, Kolkata, Hyderabad

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

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 :

  • 3+ 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
  • (ref : hirist.tech)

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