Data Engineer

Soho, London Hybrid working: 3 days in the office Tues - Thurs The Role We are seeking a Data Engineer to join our Data Team, playing a vital part in building the complex, scalable systems that power our data strategy. You will contribute to architectural discussions and deliver high-quality data solutions that bring millions of fans closer to the sports they love. This is a fantastic opportunity to develop your expertise in optimising data platforms for real-time AI/ML workloads, collaborate with experienced engineers, and make a significant impact on our business. At LiveScore Group, we’re the proud home of three of the most exciting brands in the sports and gaming world: LiveScore, LiveScore Bet and Virgin Bet. A fully owned and operated ecosystem that converges the two worlds of sports media and sports betting. We’re proud of the high ratings for our commitment to excellence and fueling fan’s passion for sport driving us to the top. We don’t just lead; we innovate. Our cutting-edge products and immersive experiences set the standard, but it’s our people who truly make the difference. Every day, our team embody our values: adaptability, teamwork, a fan-driven approach, and an ever-curious mindset that fuels our ambition. As we scale and continue to create a culture that allows all employees to thrive, we know we need the most talented people with diverse backgrounds, perspectives and skills. If you’re good at what you do, come and join us. The more inclusive we are, the more amazing experiences we can create for our users. We know that job descriptions can sometimes seem daunting, and you might not feel you tick every box. But, if you’re passionate about the role and have relevant experience, we want to hear from you!  Key Responsibilities  * Develop and deploy robust data pipelines using GCP services such as BigQuery, Dataflow, Pub/Sub and Cloud Storage. This includes integrating data from various sources, ensuring data quality and enabling real-time processing capabilities. * Design data models and manage databases effectively to support business analytics and intelligence using dimensional data-modelling principles. Use GCP database technologies such as Bigtable, Spanner or Firestore to optimise performance and scalability. * Automate data workflows and optimise data storage and processing costs within GCP. Use tools such as Cloud Composer for orchestration and apply best practices in performance tuning. * Ensure data security by implementing GCP security practices. Manage access controls, comply with data-governance policies and safeguard sensitive information. * Work closely with data engineers, business analysts, and IT teams to define data requirements and deliver comprehensive data solutions.  * Stay up to date with the latest GCP features and data-engineering technologies. Explore ways to enhance data infrastructure and contribute to the development of new data products. * Provide second-line support for pipeline failures or data quality incidents and perform fault analysis to resolve issues.  * Contribute to system-design decisions and help develop data solutions that support real-time workloads. * Partner with cross-functional teams to translate business needs into effective data solutions. * Design data systems that solve problems and improve reliability & cost-effectiveness.  * Develop and maintain robust, secure integrations with core internal systems and third-party platforms.  * Implement monitoring and alerting to ensure high system reliability and minimal downtime.  Skills, Knowledge and Experience  * Experience in data engineering or data warehousing with large-scale, complex datasets. * Experience writing complex SQL queries. * Experience with Python or a similar programming language, with the ability to turn business requirements into working solutions.  * Experience with cloud data services and technologies, ideally within the GCP ecosystem, such as Dataflow, Pub/Sub, BigQuery or Vertex AI. * Experience with Airflow environment management and Docker.  * An interest in contributing to the AI roadmap and experimenting with AI tooling, including coding agents, within the development lifecycle. * The ability to explain technical concepts clearly and concisely to technical and non-technical stakeholders. * Experience developing and optimising real-time and large-scale batch data-processing frameworks. * Experience deploying and maintaining data infrastructure using Infrastructure as Code principles and tools such as Terraform. * An understanding of data-governance, privacy and security best practices in a regulated environment. * A proactive and curious approach to identifying and resolving system inefficiencies. * The ability to work effectively with cross-functional teams and translate requirements into robust data solutions. * A strong sense of responsibility for the quality, reliability and performance of the data solutions you help create. What can we offer?  * Company Performance Bonus * Flexible Working Agreements where applicable * Private Healthcare Scheme + Employee Enhanced Assistance * Enhanced Family Leave - Maternity, Shared Parental & Adoption Leave: up to 6 months at full pay and 6 months at half pay. Paternity leave: up to 4 weeks at full pay * Subsidised Gym Membership * Annual Travel Card Loan & Ride to Work Scheme * Life Assurance (x3 salary) * Contributory Pension Plan * Virgin Family: Giving you access to exclusive Virgin offers and experiences * Thursday drinks in the office and regular socials

What you’ll do Own the global UW tables (canonical facts/dimensions for applications, decisions, features, repayments, delinquency) with clear SLAs for freshness, completeness, accuracy, and data lineage. Design for AI-agents and humans: consistent IDs, canonical events, explicit metric definitions, rich metadata (schemas, data dictionaries), and machine-readable data contracts. Build & run pipelines (batch + streaming) that feed UW scoring, real-time decisioning, monitoring, and underwriting optimization. Instrument quality & observability (alerts, audits, reconciliation, backfills) and drive incident/root-cause reviews. Partner closely with Credit Portfolio Management, Policy teams, Modeling teams, and treasury and finance teams to land features for RUE and consumer-centric models, plus regulatory and management reporting. Tech stack (what we use) Languages: SQL, PySpark, Python Frameworks: Apache Airflow, AWS Glue, Kafka, Redshift Cloud & DevOps: AWS (S3, Lambda, CloudWatch, SNS/SQS, Kinesis), Terraform; Git; CI/CD What you’ll bring Proven ownership of mission-critical data products (batch + streaming). Data modeling, schema evolution, data contracts, and strong observability chops. Familiarity with AI/agent patterns (agent-friendly schemas/endpoints, embeddings/vector search).