Data Backend Engineer
Objective of job
• With the number of connected Mercedes-Benz vehicles on the road increasing daily, the amount of data being generated and its significance is also increasing rapidly. The Vehicle Infrastructure & Data Analytics team is looking for passionate and versatile Engineers to support with the collection, storage, processing, and analysis of large amounts of vehicle data.
This position will play a key role in the development and deployment of an innovative Big Data Platform for vehicle data processing and advanced analytics. As an Engineer on the team, you'll be responsible for defining and building the data pipelines that combine vehicle data and third-party content and will enable better, faster, data-informed decision-making. As part of a larger global interdisciplinary team, you will also make strategic decisions that influence the platform and data warehouse architecture.
This is a unique opportunity to join an innovative group of engineers creating the next generation big data platform that will be accessed and used by hundreds of people across domains within Mercedes-Benz.
- Bachelor’s Degree - Computer Science, Electrical Engineering, or similar
- Experience with web technologies (Spring Boot, Maven, Mockito)
- Experience with cloud technologies like AWS or Microsoft Azure
• Specific Knowledge
- Experience with system design and specification
- Hands-on API design and data content modelling in JSON
- Knowledge about stream processing and batch oriented systems
- Very strong conceptual and analytical skills
- Team-player with strong people skills
- Experience in build and deploy code using Apache maven
- Hands-on experience in agile software development with GIT and JIRA
- Computer network security, protocols and topologies
- Experience with databases (e.g. MySQL, MS SQL, Postgres & noSQL)
- Experience in Java software development
• Architecture and design of a Big Data System in collaboration with other RD departments
• Maintain and operate a Big Data System in a cloud environment like Microsoft Azure
• Setup data pipelines and coordinate the data flow with different stakeholders
• Specify and negotiate Data and Knowledge APIs within different consumers
• Implementation of data flows within streaming and batch systems