Data Engineer, Data Platforms

IBM

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1 day ago
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Confirmed live today

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How this pay compares to similar roles

Similar $179k
$133k most similar roles pay here $232k

This listing doesn't post a salary. Most similar roles pay $142,300–$216,000.

Based on 240 similar postings.

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

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TL;DR · Data Engineer, Data Platforms

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As a Data Engineer-Data Platforms-Google - 1 within IBM Consulting, you will join a team dedicated to helping clients shape their hybrid cloud and AI journeys. You will design, build, and maintain scalable data engineering solutions and pipelines on the Google Cloud ecosystem. Your daily responsibilities include developing batch and real-time pipelines for Data Warehouses and Datalakes, optimizing data layers for efficient migration, and managing platform operations. You will utilize a technical stack including Google DataProc, DataFlow, PubSub, BigQuery, BigTable, Cloud Spanner, CloudSQL, and AlloyDB. Required skills include proficiency in open-source technologies such as Apache Beam, Airflow, dbt, Spark, Python, and Scala to solve complex data processing and infrastructure challenges for diverse business needs.

What does a Data Engineer earn?

Median $167000 from 183 postings across 57 companies.

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Skills

BigQuery DataFlow DataProc PubSub BigTable Cloud Spanner CloudSQL AlloyDB Apache Beam Apache Airflow Spark Scala Python dbt Hadoop Cloud Composer Google Cloud Storage Data Modeling

What you'll do

  • Design and develop batch and real-time data pipelines for Data Warehouse and Datalake.
  • Build and maintain data engineering solutions using Google Cloud Storage, BigQuery, and BigTable.
  • Implement data processing using DataProc with Spark/Hadoop and DataFlow with Apache Beam or Python.
  • Schedule and manage data platform operations using Google Cloud Scheduler and Cloud Composer.
  • Optimize the data layer for efficient data migration and processing using Google Cloud services.
  • Ensure the scalability and efficiency of all data pipelines to meet business requirements.
  • Integrate open-source technologies like dbt, Airflow, and Spark into the Google Cloud ecosystem.

What we're looking for

  • Proven experience designing, building, and maintaining data engineering solutions on Google's Cloud ecosystem.
  • Expertise in Google Cloud services including DataProc, DataFlow, PubSub, BigQuery, Big Table, Cloud Spanner, CloudSQL, and AlloyDB.
  • Proficiency in open-source technologies such as Apache Beam, Apache Airflow, dbt, Spark/Python, or Spark/Scala.
  • Experience developing and managing batch and real-time data pipelines for Data Warehouse and Datalake.
  • Experience scheduling and managing data platforms using Google Cloud Scheduler and Cloud Composer.
  • Experience designing and optimizing data layers for efficient data migration and data processing.
  • Bachelor's Degree.

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