Senior Data Engineer - GCP

Senior Data Engineer

Location: London - Weekly / Bi Weekly Travel to Germany

Sector: Events and Live Entertainment

Work Type: Contract - 6 Months Inside IR35 - £660 per day

My client is a leading organisation within the events and live entertainment space, delivering large-scale live experiences to millions of customers each year. With a growing digital and data function, they are investing in a modern, cloud-first data platform to power commercial insight, audience analytics, operational reporting and real-time decision-making across venues and events.

As a Senior Data Engineer, you will design, build and optimise scalable data pipelines on Google Cloud Platform. You will take ownership of core data engineering patterns, evaluate and implement modern open-source frameworks, and help shape the evolution of the organisation's cloud data architecture.

This role requires a proactive, self-starter mindset with the ability to operate independently while collaborating closely with Data Modelling, Analytics and wider technology teams.

• Design, build and maintain scalable ETL and ELT pipelines
• Develop and optimise data processing workflows on Google Cloud Platform
• Implement robust and scalable data ingestion frameworks
• Work with structured and semi-structured data sources across multiple business domains
• Collaborate closely with Data Modelling and Analytics teams to enable reliable downstream reporting and insight
• Ensure data reliability through monitoring, observability and quality controls
• Automate deployment processes and data workflows wherever possible
• Contribute to tooling decisions, framework selection and data platform standards

• Strong experience designing and building ETL and ELT pipelines in production environments
• Hands-on experience with GCP data services such as Big Query, Cloud Storage, Dataflow or equivalent
• Advanced SQL and strong data transformation capability
• Experience with orchestration tools and automated pipeline scheduling
• Experience working within modern data architectures including warehouse and lakehouse patterns
• Demonstrated ownership mindset with strong problem-solving capability

• Exposure to Data Vault 2.0 modelling concepts
• Experience optimising performance and cost within Big Query
• Experience evaluating and implementing open-source data engineering frameworks
• Experience implementing CI/CD for data pipelines