Data Analyst im Bereich Data Engineering & Solutions in Immenstaad am Bodensee bei Airbus

Job Description:

To support our team in department "Data Engineering Friedrichshafen", Airbus Defence and Space is looking for a

Data Analyst (m/w/d)

Our department provides solutions and services in the area of digitalization of the satellite engineering process. This comprises the development and deployment of Airbus DS proprietary database systems, web applications and integrated engineering solutions, as well as services such as data management, data governance and data analysis in satellite projects. We apply state-of-the-art software development techniques and address practical problems from the spacecraft engineering domain using modern AI technologies.

To strengthen our team, we are currently looking for a Data Analyst. You will be working on the design, development and commissioning of data management and analysis solutions. Together, we serve our engineering teams and support their processes from design to operation of the satellites with state-of-the-art digitalized database systems and analytics services.

Your location

At the Airbus site in Friedrichshafen, you work on innovations where others go on vacation. Enjoy the panoramic view of Lake Constance while you eat lunch in our canteen. And after work, join one of our many company sports groups to go running, sailing or skiing.

Your tasks and responsibilities

You will take on an active role in a transnational (D/F/UK) digitalization initiative, DLR and ESA studies as well as research and development projects. You will become part of a local AI community and drive the design and development of data analytics solutions and services in AIRBUS DS Space Systems.

Your main tasks include:

• Identify and understand the engineering use cases to be supported by big data, data analytics or artificial intelligence technologies.

• Describe new datasets and the input you need to provide efficient solutions.

• Build the data analytics answer regarding the needs in a cost efficient way by quickly prototyping data exploration and visualization applications around data and algorithms.

• Support the users in the analysis of the results concurring to an improvement of the overall engineering task efficiency.

• Support the department R&D/T roadmap and progress for AI related topics.

Ideally, you have first experience in a complex IT environment and are able to acquire and process data from heterogeneous sources (e.g. remote Hadoop/Spark cluster, relational and non-relational databases). You have first experience working with engineering fields (for example System Engineering, SW Engineering, Functional Engineering, Mechanical & Thermal Engineering, Space Physics), where you demonstrated good communications skills and adaptability to challenge new domains of competence. You know the basics of developing (web-based) applications and you can integrate intoa collaborative development environment (GIT versioning, issue tracking systems, AGILE process and testing & documentation frameworks). You use those applications at an early prototype state to iterate with your end users/engineering experts.

You are curious and open minded and a very good listener. You prefer to work on several topics simultaneously. You are an empowered, autonomous and proactive person with the ability to communicate with multiple interfaces, and enjoy to work within a transnational team and environment.

Desired skills and qualifications

As the successful candidate, you should be able to demonstrate some of the following skills and qualities:

• Completed studies in Data Science, Computer Science, Software Development or similar

• Communication & Cooperation

  • Good communication skills, a proactive mind-set and the ability to work in an international environment.

  • Ability to define and manage work packages autonomously and work in close collaboration with our internal users.

• Data Science, Development & Programming

  • Strong background in descriptive statistics (clustering, dimension reduction, distribution fitting) and inferential/predictive statistics (Machine Learning such as Neural Networks, SVM, Random-Forest)

  • Experience in data exploration and interpretation, how to identify and model trends and deal with high dimensionality.

  • Experience with research methods (graph theory, numerical optimization, surrogate modeling) to address challenges beyond data analysis, with pragmatic solutions as well (splines modeling, dichotomy optimization).

  • Experience in at least one programming language (R, Python) that allows you t