Position: Cloud Data Engineer for Autonomous Driving
Company: Luxoft
Experience required: 5y
Category: Java
English level: upper
Published: 2020-02-01T00:00:00+02:00

There are millions of cars on the road today with solutions designed & implemented by us focusing on Autonomous Drive, Embedded Applications, Digital Cockpit, Connected Mobility & overall excellence in delivery.

The race is on to build fully autonomous vehicles. The first automaker to achieve the highest level of autonomous driving (AD) by building the better driver will not only lead the market, but also define transportation of the future. To do this, AD research and development (R&D) engineers and IT teams must collect and store a staggering amount of sensory data for analysis and interpretation to produce control systems that perceive information and accurately navigate the vehicle.

Our Robotic Drive platform provides toolkit and expertise that AD R&D and IT teams need to collect, manage and analyze massive amounts of sensor data from around the globe at significant speed to reduce time- and cost-to market in the race to develop fully autonomous vehicles.

Azure Data Engineer supports Robotic Drive opportunities mainly for the following phases
• Technical solution implementation within Robotic Drive offering engineering
• Pre-sales activities; acting as Subject Matter Expert in this phase
• Responding to customer request for proposals with a competitive design
Responsibilities:
• Design Robotic Drive based solutions with focus on cloud (focus Azure) to effectively bring innovation and state-of-the-art methods and approaches into the development and testing of autonomous driving algorithms.
o Implementing data transformation processes in the Robotic Drive solution domain
o Support data driven cloud applications and projects in the area of data science
• Build and integrate Robotic Drive AI& storage solutions, toolkits and accelerators on Azure marketplace (high data volume ingests, distributed processing of native automotive formats, geo-distributed data lake & volume partitioning)
• Development, Virtualization, Automation, Monitoring, Auditing, Continuous Improvement) to enable seamless provisioning of services for end-to end autonomous driving storage, compute and AD development at scale based on cloud native services
o Productionize data ingest, secure and fully automated on large sensor data sets from R&D vehicles into geo-distributed data lake
o High performance and scalable geo-distributed data organization pattern/volume partitioning providing data to end users on multi-locations across regions
o Store, analyze and refine automotive data on hundreds of PB scale natively with distributed/parallel processing on sensor level (ROSbag, MDF4, ADTF)
• Workflow integration, toolkit and applications containerization
• Develop prototypes & proof-of-concept solutions in support of presales activities
Mandatory Skills:
• Significant experience in enterprise cloud solutions in Azure (or AWS)
• Knowledge of and experience with cloud based AI services
• Ideally relevant cloud provider certifications i.e. certified Azure Data Engineer
• Bachelor or Master degree required in information technology, computer science or similar.
• Minimum 3+ years of experience with Big Data Hadoop distributions and innovative technologies in Hadoop ecosystem (e.g. HDFS, Spark, Hive, HBase)
• 2+ years hands-on experience in Docker, Kubernetes, containerization
• Basic system administration, platform build and operations (Linux, Windows, Ubuntu, RedHat Openshift, MapR)
• 2+ years experience in Big Data programming (Java, Spark, Python)
• Experience with cloud native services best practices, principles and software products
• Working experience with high performance computing architectures and relevant software products
• Strong customer focus, assertiveness and precise method of operation
• Possesses an understanding of architectural dependencies of technologies in the customer's analytic environments
• Able to communicate and present internally and externally in a confident manner
• Highly motivated team player
Nice-to-Have Skills:
• Basic understanding and some hands-on experience of Hadoop and it's ecosystem products (Spark, Jupyter)
• At least con Know-how in automotive formats (ROSbag, ASAM MDF4, HDF5, ADTF)
• Conceptual, better hands-on software development experience.
• Experience with simulation technologies, ideally in the automotive domain
Languages:
English: Advanced/Fluent