Senior Software Developer for Analytics

Accountabilities

• Design technical solutions that integrate data pipelines, analytical models, and user-facing experiences into cohesive products.


• Break complex analytics and Artificial Intelligence (AI) feature areas into clear engineering plans and identify technical risks early.


• Lead code and technical design reviews, improving architecture, code quality, testing practices, and engineering standards.


• Partner with data scientists, AI engineers, and product managers to shape experiments and transition successful prototypes into production-ready systems.


• Mentor junior and developing engineers, sharing expertise in system design, debugging, technical decision-making, and stakeholder communication.


• Own end-to-end analytical solution design, including data contracts, feature stores, model endpoints, and client integrations.


• Design and evolve solutions on modern cloud data platforms such as Snowflake, Databricks, or Palantir Foundry.


• Evaluate architecture and tooling decisions based on cost, risk, scalability, and business value.


• Monitor developments in analytics and AI platforms and recommend new technologies when they provide meaningful value.


• Select appropriate integration patterns and conduct Proofs of Concept (PoCs) to validate technical approaches and scalability.


• Make informed build-versus-reuse decisions while balancing experimentation speed with reliability and long-term maintainability.


• Communicate technical direction and trade-offs effectively with senior engineers, data scientists, AI engineering teams, product partners, and other stakeholders.

• Bachelor’s degree in Computer Science or a related field with approximately 8 years of relevant software development experience, or 6 years with a Master’s degree, or 3 years with a PhD; equivalent professional experience is also considered.


• Proven experience owning delivery of complex, multi-team software or data engineering initiatives.


• Strong production experience with Python, SQL, and Git, particularly in the development and operation of data pipelines.


• Hands-on experience with a modern cloud data platform such as Snowflake, Databricks, Palantir Foundry, or an equivalent technology.


• Strong understanding of scalable data architecture and integration patterns, including Extract, Transform, Load (ETL), Extract, Load, Transform (ELT), batch processing, and streaming.


• Experience with JavaScript or TypeScript and React for developing customer-facing applications and interfaces.


• Strategic mindset combined with the ability to remain hands-on and independently drive complex engineering initiatives.


• Strong mentoring skills and a genuine interest in helping engineers develop their technical capabilities.


• Clear communication skills, with the ability to explain technical concepts and trade-offs to both technical and non-technical stakeholders.


• Strong decision-making skills in ambiguous environments, while maintaining awareness of broader business and product objectives.


• Collaborative approach and ability to build effective working relationships with data science, AI engineering, and product teams.


• Experience in automotive, consumer insights, or analytics-driven Software as a Service (SaaS) environments is desirable.


• Experience mentoring engineers and leading technical design reviews is desirable.


• Experience with PySpark or another distributed data processing framework is a plus.


• Familiarity with Continuous Integration and Continuous Deployment (CI/CD), observability tools, and infrastructure-as-code is desirable.


• Experience with cloud infrastructure across Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP) is a plus.


• Exposure to deploying AI or Machine Learning (ML) models into production analytics use cases is desirable.


• Working knowledge of HTML, CSS, and data visualization libraries is beneficial.

• Full-time position.


• Remote working arrangement within the United Kingdom.


• Opportunity to work on sophisticated analytics and data products with global customer impact.


• Exposure to modern cloud data platforms and AI-driven analytics applications.


• Opportunity to influence architecture, engineering standards, and technical direction.


• Significant ownership over complex feature areas and end-to-end solution design.


• Opportunity to mentor engineers and contribute to the development of the wider engineering team.


• Collaborative environment involving software engineering, data science, AI engineering, and product teams.


• Opportunity to contribute to innovative, data-driven solutions within the automotive and consumer insights space.

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