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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 solutions
Cloud & 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 code
Data 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