Overview
In this role you help tailor Tesco’s experiences by building real-time, personalised recommendations and offers across web, mobile, and in-store channels. You will work with real-time data, ML, and large-scale distributed systems to turn insights into fast decisions. Collaborating with product, data science, and analytics, you’ll tackle streaming data, low-latency services, and ML-powered systems at scale. This position offers impact on how millions of customers discover, shop, and save with Tesco, within a supportive, flexible environment.
Pay / Benefits
- Annual bonus up to 20%
- Holiday from 25 days + personal day + bank holidays
- Private medical insurance
- Maternity and adoption leave
- Paternity leave
- 24/7 virtual GP service and EAP for family wellbeing
Responsibilities
- Build low-latency, high-throughput services for personalisation
- Develop Java / Spring Boot microservices with REST/gRPC APIs
- Work with Kafka and event-driven architectures
- Build pipelines using Apache Flink and Apache Beam
- Integrate ML models and feature stores
- Work with NoSQL databases and Redis caching
- Use Apache Camel for integration where required
- Collaborate with product, data science, and analytics teams
- Write automated tests and improve reliability
- Monitor systems using New Relic, Splunk, and metrics platforms
- Support CI/CD pipelines and deployments
- Contribute to experimentation (A/B testing)
Key requirements
- Strong Java backend experience
- Experience building microservices and APIs
- Understanding of event-driven systems
- Familiarity with stream processing concepts
- Knowledge of distributed systems
- Strong communication and teamwork skills
- Interest in data-driven personalisation systems
- Strong communication
- Teamwork
- Problem-solving
- Java backend
- Microservices
- REST/gRPC APIs
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