Offers “Atos”

Expires soon Atos

Data Engineer

  • Internship
  • USA
  • IT development

Job description



About Atos

Atos is a global leader in digital transformation with 110,000 employees in 73 countries and annual revenue of € 12 billion. European number one in Cloud, Cybersecurity and High-Performance Computing, the Group provides end-to-end Orchestrated Hybrid Cloud, Big Data, Business Applications and Digital Workplace solutions. The Group is the Worldwide Information Technology Partner for the Olympic & Paralympic Games and operates under the brands Atos, Atos|Syntel, and Unify. Atos is a SE (Societas Europaea), listed on the CAC40 Paris stock index.

The purpose of Atos is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.

 

 

 

 

 

 

Position:

 

Data Engineer

 

 

Location:

 

 

US Wide

 

Job Description:

 

We are looking for a savvy Data Engineer to join our growing team of analytics specialists. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for multi-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 architects, data analysts 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. This position will collaborate with the office of the Digital Workplace Chief Innovation Officer.

 

Responsibilities :

 

·  Build and maintain efficient data pipeline architecture,
·  Assemble large, sophisticated 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 measurable insights into customer acquisition, operational efficiency and other key business performance metrics.
·  Work with partners 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.
·  Build 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 specialists to strive for greater functionality in our data systems.

 

Requirements :

 

·  Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
·  5+ years of experience in a Data Engineer
·  Must be able to work from home successfully with a distributed team
·  Sophisticated working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
·  Must have sophisticated solid understanding of Google BigQuery and Google Cloud SQL
·  Practical experience handling Google Cloud SQL and Google Biq Query platforms, including integration
·  Understanding of performing ETL work within Google Biq Query
·  Job automation using Googles DataFlow and DataProc
·  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 see 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 multi-functional teams in a multifaceted environment.
·  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, MySQL and Cassandra.
·  Experience with data pipeline and workflow management tools
·  Experience with cloud services: Google and/or AWS
·  Experience with object-oriented/object function scripting languages: Python, PHP, Java, C++, Scala, etc.

Here at Atos, we want all of our employees to feel valued, appreciated, and free to be who they are at work. Our employee lifecycle processes are designed to prevent discrimination against our people regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes them unique. Across the globe, we have created a variety of programs to embed our Atos culture of inclusivity, and work hard to ensure that all of our employees have an equal opportunity to contribute and feel that they are exactly where they belong.