Data Engineer, Data Platforms

IBM

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Work type: On-site
Location: —
Posted: 1 day ago
Freshness: Confirmed live today

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How this pay compares to similar roles

Similar $169k

$125k most similar roles pay here $213k

This listing doesn't post a salary. Most similar roles pay $133,718–$203,636.

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 - 2 within IBM Consulting, you will design, build, and maintain data engineering solutions on Google's Cloud ecosystem. You will develop scalable batch and real-time data pipelines for Data Warehouses and Datalakes, ensuring efficient data migration and processing. Your daily work involves utilizing Google Cloud services including DataProc, DataFlow, PubSub, BigQuery, Big Table, Cloud Spanner, CloudSQL, and AlloyDB. You will manage data platforms using Google Cloud Scheduler and Cloud Composer. Technical requirements include proficiency in open-source tools such as Apache Beam, Apache Airflow, dbt, Spark/Python, and Spark/Scala. You will solve complex data engineering problems by optimizing data layers and integrating diverse technologies to meet specific business needs within a consulting framework.

What does a Data Engineer earn?

Median $162000 from 188 postings across 59 companies.

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Skills

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

What you'll do

Design and develop batch and real-time data pipelines for Data Warehouses and Datalakes.
Build and maintain data engineering solutions using Google Cloud Storage, BigQuery, and BigTable.
Implement data processing using Spark, Hadoop, Apache Beam, and Python.
Schedule and manage data platforms using Google Cloud Scheduler and Cloud Composer.
Optimize the data layer for efficient data migration and processing.
Ensure the scalability and efficiency of all data pipelines to meet business needs.
Integrate open-source technologies like dbt and Airflow with Google Cloud services.

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 processing.
Bachelor's Degree.

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