Direct Client Need GCP Data Engineer - Mountain View CA

 (10+ years exp)
$100k – $110k
Published: 6 days ago

Job Location

Job Type

Contract

Visa Sponsorship

Available

Remote Work Policy

In office - WFH flexibility

Relocation

Allowed

Skills

Python
Java
Javascript
Full Stack Development
Engineering
JSON / XML / HTML / Javascript / JQuery
GCP
Google GCP
Google Cloud Platform (GCP)

The Role

Job title: GCP Data Engineer

Location: Mountain View, CA (Day 1 onsite)

Key SKills : Data Fusion , GCP, FullStack Java or Backend Java Development , Strong NoSQL DB ,

Required Skills and Experience

· Must have Experience in relational Database –No SQL, Oracle, ETL Tools (such as Informatica, Apache Beam, Kafka) etc.

· Must have Experience in Google Cloud Platform (BigQuery, DataProc, DataFlow)

· Must have experience in Java full stack/ Back end developing, any scripting/programming language as following: Java/Python/Go

· Having relative experience in declarative CI/CD (Jenkins, Azure DevOps)

· Having relative experience in Databases: NOSQL and SQL

· Have a strong engineering mindset to automate tasks, identify use cases, test cases, improve the system, PR/Incident resolution and deployments

· Excellent communication skills

Description:

· You will be responsible for building and running the data processing pipeline on Google cloud platform

· Work with implementation teams from concept to operations, providing deep technical expertise for successfully deploying large scale data solutions in the enterprise, using modern data/analytics technologies on GCP

· Work with data team to efficiently use GCP to analyse data, build data models, and generate reports/visualizations

· Integrate massive datasets from multiple data sources for data modelling

· Implement methods for DevOps automation of all parts of the build data pipelines to deploy from development to production

· Formulate business problems as technical data problems while ensuring key business drivers are captured in collaboration with product management

· Design pipelines and architectures for data processing

· Extract, load, transform, clean and validate data

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