Data Engineer-Must have strong GCP experience-Inside IR35

Data Engineer-Must have strong GCP experience-Inside IR35 Data Engineer (GCP) We are working with a client delivering a large-scale Data Strategy programme and are looking for a skilled Data Engineer to help shape the next generation of their data platform. You will play a key role in designing and building scalable, resilient and reusable data pipelines on Google Cloud Platform (GCP), enabling faster and more reliable data delivery across multiple product teams. This is a great opportunity for someone who combines strong technical expertise with a collaborative approach, and enjoys working in complex, enterprise-scale environments with high standards for quality and reliability. Key Responsibilities Design and build scalable, reusable data pipeline templates across multiple data domains Standardise ingestion and transformation using configuration-driven frameworks Embed data quality checks by default (schema validation, completeness, freshness, thresholds, alerting) Improve pipeline resilience, monitoring, observability and recovery mechanisms Integrate AI/ML capabilities where appropriate (e.g. anomaly detection, intelligent monitoring) Support delivery of a wider Data Strategy programme, improving consistency and data quality Ensure pipelines are production-ready, documented and suitable for BAU handover Collaborate closely with Data Product, Analytics Engineering and Data Science teams Technical Skills & Experience Programming & Data Engineering Strong experience with Python, Scala and SQL Solid background in data modelling and ETL/ELT pipelines Experience building enterprise-grade data solutionsCloud & Platform Hands-on experience with Google Cloud Platform (GCP), ideally including: BigQuery Dataflow Pub/Sub Composer Cloud Run / App Engine Experience with CI/CD, automated testing and infrastructure as codeData Quality & Monitoring Experience implementing data quality frameworks, observability tooling and monitoring solutions Preferred Experience Building reusable pipeline frameworks for large, multi-domain platforms Delivery within enterprise data transformation programmes with strong SLAs Exposure to AI-enabled data pipelines (e.g. anomaly detection, intelligent monitoring) Experience with data quality at scale Understanding of MLOps or deploying ML models into production Must-Haves Strong hands-on experience with GCP, Python and Scala Proven track record delivering production-grade data pipelines Deep expertise across modern cloud data platforms Strong problem-solving mindset and willingness to learn