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Senior Data Engineer - Vancouver

  • Vancouver, BC, Canada

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Original job description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

  • Strong/expert Spark (PySpark) Using Jupyter Notebooks, Colab or DataBricks (preferred)  
  • Hands-on data pipeline development, ingest patterns in Azure  
  • Orchestration tools, ADF or Airflow   SQL   Denormalized Data modeling for big data systems 

Responsibilities and essential job functions include but are not limited to the following:    

  • Demonstrate deep knowledge of the data engineering domain to build and support non-interactive (batch, distributed) & real-time, highly available data, data pipeline, and technology capabilities  
  • Build fault-tolerant, self-healing, adaptive, and highly accurate data computational pipelines  
  • Provide consultation and lead the implementation of complex programs  
  • Develop and maintain documentation relating to all assigned systems and projects  
  • Tune queries running over billions of rows of data running in a distributed query engine  
  • Perform root cause analysis to identify permanent resolutions to software or business process issues

Job Description

Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets.

Job Description - Grade Specific

The involves leading and managing a team of data engineers, overseeing data engineering projects, ensuring technical excellence, and fostering collaboration with stakeholders. They play a critical role in driving the success of data engineering initiatives and ensuring the delivery of reliable and high quality data solutions to support the organizations data driven objectives.

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Make it real | www.capgemini.com

More about this job

Responsibilities

The Senior Data Engineer will build and support highly available, fault-tolerant data pipelines and computational infrastructure. They are responsible for leading data engineering projects, ensuring technical excellence, and performing root cause analysis to resolve complex system issues.

Requirements

Candidates must possess expert-level knowledge in Spark, PySpark, and data modeling for big data systems. Proficiency in Azure, orchestration tools like ADF or Airflow, and experience in tuning queries over large datasets are required.

Skills

  • Spark
  • PySpark
  • Jupyter Notebooks
  • Colab
  • DataBricks
  • Data Pipeline Development
  • Azure
  • ADF
  • Airflow
  • SQL
  • Data Modeling
  • Big Data Systems
  • Distributed Query Engine
  • Root Cause Analysis

Visa sponsorship

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Categories

  • Data & Analytics
  • Technology
  • Software
  • Engineering
  • Consulting

Keywords

  • Data Engineering
  • Spark
  • PySpark
  • Jupyter Notebooks
  • Colab
  • DataBricks
  • Data Pipeline
  • Azure
  • ADF
  • Airflow
  • SQL
  • Data Modeling
  • Big Data
  • Distributed Systems
  • Batch Processing
  • Real-time Data
  • Fault-tolerant
  • Query Tuning
  • Root Cause Analysis
  • Software Engineering
  • Cloud Computing
  • Data Infrastructure
  • Leadership
  • Consulting
  • Technology Transformation

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