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ID:  116828
Location: 

Norfolk Va, US

Data Engineer

 

CMA CGM Group, founded by Jacques R. Saadé, is a leading worldwide shipping & logistics group.

Now headed by Rodolphe Saadé, CMA CGM reinvents transport and logistics in order to offer an integrated maritime, port and land service that exceeds its customers' expectations. 

Present in over 160 countries through 755 offices, 750 warehouses, equipped with a young and diverse fleet of 511 vessels, CMA CGM serves 420 of the world's 521 commercial ports and operates on more then 200 shipping lines. The group currently employs 110,000 people worldwide, including nearly 2,400 in Marseille, in its headquarters in Marseilles.

 

 

 

Position Summary

Our company is searching for a savvy Data Engineer to join our growing team of analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, database architect, BI developers and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.

 

Position Responsibilities

  • Create and maintain optimal data pipeline architecture,
  • Assemble large, complex data sets that meet functional / non-functional business requirements.
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
  • Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
  • Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  • Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
  • Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
  • Work with data and analytics experts to strive for greater functionality in our data systems.
  • Assembling large, complex sets of data that meet non-functional and functional business requirements
  • Identifying, designing, and implementing internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes  
  • Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS and SQL technologies
  • Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition 
  • Working with stakeholders including data, design, product, and executive teams and assisting them with data-related technical issues
  • Working with stakeholders including the Executive, Product, Data and Design teams to support their data infrastructure needs while assisting with data-related technical issues 
  • Ability to build and optimize data sets, ‘big data’ data pipelines and architectures 
  • Ability to perform root cause analysis on external and internal processes and data to identify opportunities for improvement and answer questions 
  • Excellent analytic skills associated with working on unstructured datasets 
  • Ability to build processes that support data transformation, workload management, data structures, dependency, and metadata
     

Skill Sets / Education & Experience

 Required

An ideal candidate would have 1) a passion for technology and a desire to use technology to improve operations and customer/employee experience; 2) empathy and experience working with coworkers from diverse backgrounds 3) the ability to present information in an insightful and structured manner.

  • 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
  • Experience with big data tools: Hadoop, Spark, Kafka, etc.
  • Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
  • Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
  • Experience with AWS cloud services: EC2, EMR, RDS, Redshift
  • Experience with stream-processing systems: Storm, Spark-Streaming, etc.
  • Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  • Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets.
  • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
  • Strong analytic skills related to working with unstructured datasets.
  • Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
  • A successful history of manipulating, processing, and extracting value from large disconnected datasets.
  • Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
  • Strong project management and organizational skills.
  • Experience supporting and working with cross-functional teams in a dynamic environment.

 

Come along on CMA CGM’s adventure !

 

 

 

 

 

 

 

 

 

 


Nearest Major Market: Hampton Roads

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