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