At Motion Applied, we accelerate the response to the world's rapid change, pioneering solutions in automotive, transportation, and motorsport to reduce the carbon footprint through electrification, telemetry, control, and analytics., As a Software Engineer in the Data Platforms Team, you will design and deliver complex products and solutions for our ATLAS (Advanced Telemetry Linked Acquisition System) suite and related systems. The software enables race engineers and strategists to access powerful, race winning insights in F1 and other motorsport series by capturing, visualizing, and modeling real time and historic data.,
Collaborate closely with Product Managers and Field Application Engineers to understand and resolve race issues
Analyze user requirements for validity and feasibility
Detect, document, and track software defects and inconsistencies
Apply quality assurance principles throughout the Agile product lifecycle
Identify and implement continuous improvement opportunities, in collaboration with the Data Platforms team
Maintain unit test case code coverage meeting or exceeding company standards
Support pull requests, peer reviews, and knowledge transfer alongside other developers
Contribute to release planning and burndowns by providing development estimates
Write technical documentation
Identify risk and raise appropriate escalations when required
First class degree or upper 2nd in Computer Science or a similar technical field of study (or equivalent practical experience)
Thorough understanding of software engineering principles
Proficiency in C#.NET
Experience with the WPF framework
Experience with SQL
Experience with Git version control and branching strategies
Familiarity with CICD pipelines, preferably Azure DevOps
Good understanding and practice of agile project management frameworks
Ability to work both as part of a team and independently
High attention to detail and solid analytical skills
Experience with graphics APIs (e.g., DirectX or similar)
Experience in C++/CLI
Experience with database/application scaling, optimization, and monitoring
Experience with time series databases
Familiarity with message brokers such as Kafka
Experience and understanding of building products on cloud infrastructure such as AWS, Azure, and GCP, and microservices
Interest and ability to learn other coding languages as needed (e.g., Python, Angular, React)
Experience with dependency injection frameworks (e.g., Autofac)
Experience in distributed computing, machine learning, data science
Experience with building data pipelines and data streaming applications
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