Description de l'offre
Airframe Data Analytic Engineer
Airbus AOSL Getafe
Airbus is a leading aircraft manufacturer with the most modern and comprehensive family of airliners on the market, ranging in capacity from 100 to more than 500 seats. Airbus champions innovative technologies and offers some of the world's most fuel efficient and quiet aircraft. Airbus has sold over 13.800 aircraft to more than 360 customers worldwide. Airbus has achieved more than 8,000 deliveries since the first Airbus aircraft entered into service. Headquartered in Toulouse, France.
Airbus is a global leader in aeronautics, space and related services. In 2017, it generated revenues of € 67 billion and employed a workforce of around 130,000. Airbus offers the most comprehensive range of passenger airliners from 100 to more than 600 seats. Airbus is also a European leader providing tanker, combat, transport and mission aircraft, as well as Europe's number one space enterprise and the world's second largest space business. In helicopters, Airbus provides the most efficient civil and military rotorcraft solutions worldwide.
Our people work with passion and determination to make the world a more connected, safer and smarter place. Taking pride in our work, we draw on each other's expertise and experience to achieve excellence. Our diversity and teamwork culture propel us to accomplish the extraordinary - on the ground, in the sky and in space.
Description of the job
A vacancy for a Airframe Data Analytic Engineer has arisen within AIRBUS in Getafe.
The successful applicant will join Engineering
Within the newly created Airframe Data Analytic (ADA) Team, you will contribute to the Airbus Digital transformation by supporting the deployment of Data analytics for the whole Airframe engineering community.
As for the other members of this central team, your mission will be composed of two main activities:
· Supporting key change projects within Airframe perimeter that rely on advanced data analysis to improve the standard ways of working
· Building the transverse referential for data analytics in Airframe engineering
Technical topics considered are covering the whole perimeter of Airframe engineering (Stress, Design, Fatigue & Damage Tolerance, Electrical and mechanical system installation) and its interfaces with other functions (other engineering domains, manufacturing, customer services…) and focusing on how data analytics (from data exposure to machine learning) can bring value to the business.
Activities will request to use/develop data analytics capabilities fitting with business needs using appropriate techniques (python/R coding, use of airbus cloud platform…)
The team is acting in a self-organized mode since its creation enabled by a strong basis of shared values (Honesty, Trust, open-mindset, responsibility…). The team is a key actor of the Airframe digitalisation transformation journey and is part of the Airframe engineering big data network.
Tasks & accountabilities
Your main tasks and responsibilities will include:
· Providing technical leadership to big data projects to support business transformation
· Use/develop data analytics capabilities fitting with business needs using appropriate techniques
· Acting as a key user of the Big Data platforms and provide support to the Airframe engineering community
· Establishing and maintain collaborative network within Airframe engineering
· Promoting the new big data technology to the Airframe networks
· Establishing and maintain collaborative network between Engineering and other functions: Manufacturing, Quality, Customer Services…
· Contributing to the vision & strategy of Airframe digitalization/data analytics
· Supporting and developing new digitalization initiatives
· Contributing to the Self-organized Team
· Educated to Degree or an equivalent qualification preferably in the scope of data analytics
· Experience in Data Analytic Process application (EDA, data wrangling, data visualisation)
· Experience in building machine learning systems based on the state-of-art algorithms
· A first experience of data analytics application in an industrial environment would be a plus.
· Ability to influence all stakeholders and customers
· Ability to communicate technical subjects effectively and accurately to non-specialists
· Open-mindset to new technologies and new ways of working
· Eager to learn/apply advanced data analytics capabilities
· Adaptive to change quickly in the self-organising culture
· English advanced is mandatory
· Overall knowledge of data analytics process and standard toolset
· Coding experience in Python is essential
· Knowledge and Experience in querying SQL databases
· Experience in deep learning would be a plus