Data Engineer, Google Cloud Platforms

IBM

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Quick summary

Work type
On-site
Location
San Francisco, CANew York, NY
Posted
22 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

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How this pay compares to similar roles

Similar $163k
$113k $208k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $126,750–$198,431.

Based on 240 similar postings.

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About IBM

IBM is a US-based global technology company providing hybrid cloud, AI, consulting, enterprise software, and IT infrastructure products and services.

IBM currently has 265 open roles on FindRole.

Listed pay typically runs $180,812–$217,000 across 11 roles with salary data.

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At a glance

TL;DR · Data Engineer, Google Cloud Platforms

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As a Data Engineer - Google Cloud Platforms, you will join the team to design, build, and maintain robust data engineering solutions within the Google Cloud ecosystem. Your primary responsibilities involve designing and developing batch and real-time data pipelines for Data Warehouse and Datalake environments. You will build and maintain solutions using Google Cloud Storage, BigTable, BigQuery, DataProc with Spark and Hadoop, and Google DataFlow with Apache Beam or Python. Additionally, you will manage the data platform using Google Cloud Scheduler and Cloud Composer, implement data migration solutions, and optimize the data layer using BigQuery, Big Table, and Cloud Spanner. This role focuses on ensuring efficient data storage, retrieval, and seamless data transfer between systems across various Google services.

What does a Data Engineer earn in California?

Median $187700 from 41 postings across 21 companies.

See salary data

Skills

BigQuery Dataflow DataProc PubSub Cloud Composer Airflow Spark Hadoop Apache Beam Python Cloud Spanner BigTable Cloud Storage Data Pipelines

What you'll do

  • Design and develop batch and real-time data pipelines using DataProc, DataFlow, PubSub, BigQuery, and BigTable.
  • Build and maintain data engineering solutions using Google Cloud Storage, Spark, Hadoop, and Apache Beam.
  • Schedule and manage data platform operations using Google Cloud Scheduler and Cloud Composer.
  • Develop and implement data migration solutions to ensure seamless data transfer between systems.
  • Design and optimize the data layer using BigQuery, BigTable, and Cloud Spanner for efficient storage and retrieval.

What we're looking for

  • Expertise in designing and maintaining data engineering solutions on Google's Cloud ecosystem.
  • Experience building batch and real-time data pipelines using DataProc, DataFlow, PubSub, BigQuery, and BigTable.
  • Proficiency in using Google Cloud Storage, Spark, Hadoop, Apache Beam, and Python.
  • Ability to schedule and manage data platforms using Google Cloud Scheduler and Cloud Composer (Airflow).
  • Experience developing and implementing data migration solutions using Google services.
  • Skill in designing and optimizing data layers using BigQuery, BigTable, and Cloud Spanner.
  • Must be located in the United States of America.

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