Motorsports Senior Data Processing Engineer

JR United Kingdom; Northampton; On-site; GBP 50,000 - 90,000; Full time

Job summary

An established industry player is looking for a Senior Data Processing Engineer to join their innovative Aero Innovation team. This role focuses on developing complex data pipelines and systems that enhance aerodynamics for motorsports and high-performance vehicles. You'll collaborate with a multidisciplinary team to tackle technical challenges, ensuring data integrity and optimizing performance. This position offers a unique opportunity to drive innovation and contribute to the future of motorsports while gaining valuable experience in a dynamic environment. If you're passionate about data engineering and eager to make an impact, this role is for you.

Qualifications

• 5+ years of experience in data engineering or related fields.
• Proficiency in Python, C++, and Java is essential.
• Experience with Kafka, Flink, and Databricks is preferred.

Responsibilities

• Architect and maintain scalable data pipelines for large data volumes.
• Collaborate with cross-functional teams to develop efficient data solutions.
• Ensure data integrity and quality through automated validation.

Skills

Python

C++

Java

Data Engineering

Analytical Skills

Troubleshooting

Education

Bachelor's degree in Computer Science

Master's degree in relevant fields

Tools

Kafka

Flink

Databricks

SQL

MongoDB

AWS

Azure

Job description

Motorsports Senior Data Processing Engineer, Northampton

Client: General Motors

Location: Northampton, United Kingdom

Job Category: Other

EU work permit required: Yes

Job Views: 3

Posted: 05.05.2025

Expiry Date: 19.06.2025

Job Description

We are seeking a highly skilled and motivated Senior Data Processing Engineer to join the Aero Innovation team within the Motorsports Aerodynamic Department. Your primary responsibility will be to develop complex data pipelines and data-processing systems that enhance our aerodynamics development activities for motorsport and high-performance production vehicles. You will work in a multidisciplinary team to design, develop, and optimize solutions to technical challenges, contributing significantly to our competitiveness.

Joining GM Motorsports will provide valuable experience and exposure. You will have opportunities to showcase your talents, apply your skills, drive innovation, and connect racing lessons to production vehicles. Collaborate cross-functionally with partners and help shape the future of motorsports.

What You’ll Do

• Architect, design, build, and maintain scalable data pipelines for large volumes of data from multiple sources.
• Integrate data from various platforms and systems, including on-premises and cloud databases, data lakes, APIs, and third-party vendors.
• Ensure data integrity, consistency, and quality through automated validation and monitoring.
• Identify and optimize performance bottlenecks in data workflows.
• Collaborate with Data Scientists, Product Managers, Engineers, and Aerodynamicists to develop efficient data solutions.
• Write clean, maintainable, and well-documented code following best practices.
• Prepare and deliver technical reports and presentations to stakeholders.

Qualifications

Required:

• Bachelor’s degree in Computer Science, Data Science, or related field.
• 5+ years of experience in data engineering or related fields.
• Proficiency in Python, C++, Java.
• Experience with Kafka, Flink, Databricks.
• Knowledge of distributed computing systems like SLURM, LSF.
• Experience with relational and non-relational databases (SQL, MongoDB).
• Familiarity with AWS and Azure cloud platforms.
• Strong analytical and troubleshooting skills.
• Excellent interpersonal skills for collaboration.

Preferred:

• Master’s degree in relevant fields.
• Experience in motorsports industry.
• Knowledge of data governance, privacy, security practices.
• Experience with HPC architecture, instrumentation, and Data Acquisition systems.
• Experience developing live streaming data pipelines.
• Familiarity with aerodynamic testing and practices.