Data Engineer (GCP)

As a Data Engineer, you'll design, build, and operate scalable, reliable data pipelines and data infrastructure. Your work will ensure high-quality data is accessible, trusted, and ready for analytics and data science - powering business insights and decision-making across the company.

What you'll do

• Build and maintain data pipelines for ingestion, transformation, and export across multiple sources and destinations
• Develop and evolve scalable data architecture to meet business and performance requirements
• Partner with analysts and data scientists to deliver curated, analysis-ready datasets and enable self-service analytics
• Implement best practices for data quality, testing, monitoring, lineage, and reliability
• Optimise workflows for performance, cost, and scalability (e.g., tuning Spark jobs, query optimisation, partitioning strategies)
• Ensure secure data handling and compliance with relevant data protection standards and internal policies
• Contribute to documentation, standards, and continuous improvement of the data platform and engineering processes

• 5+ years of experience as a Data Engineer, building and maintaining production-grade pipelines and datasets
• Strong Python and SQL skills with a solid understanding of data structures, performance, and optimisation strategies
• Familiarity with GCP and ecosystem knowledge: BigQuery, Composer, Dataproc, Cloud Run, Dataplex
• Hands-on experience with orchestration (like Airflow, Dagster, Databricks Workflows) and distributed processing in a cloud environment
• Experience with analytical data modelling (star and snowflake schemas), DWH, ETL/ELT patterns, and dimensional concepts
• Experience with data governance concepts: access control, retention, data classification, auditability, and compliance standards
• Familiarity with CI/CD for data pipelines, IaC (Terraform), and/or DataOps practices
• Experience building observability for data systems (metrics, alerting, data quality checks, incident response)