Data engineer

We are looking for a Google Cloud Platform (GCP) Data Engineer who will lead the engineering delivery and technical direction for a scalable multitenant data integration platform on Google Cloud Platform GCP The platform uses Managed Airflow Composer to orchestrate ETL pipelines and enables reliable movement of data from source systems through the platform into downstream vendor systems Youll guide the team in building high quality ETLs improving automation and deployment pipelines and implementing endtoend data lineage with clear visual traceability of data movement

• Own the technical roadmap for the platform aligning engineering outcomes to business priorities and operational resilience
• Lead solution design for new integrations and platform capabilities balancing pace with long term maintainability
• Set engineering standards coding testing documentation observability security and ensure consistent adoption across the team
• Provide hands-on contribution where needed critical ETLs framework components design spikes performance fixes
• Design and develop robust ETL pipelines orchestrated in Airflow including scheduling strategies dependency management retries backfills and processing
• Establish patterns for onboarding new source systems and delivering data to downstream vendor systems with strong reliability and traceability
• Drive data quality controls validation reconciliation exception handling and operational runbooks
• Evolve the multitenant architecture tenant isolation configuration management metadata driven pipelines and scalable runtime patterns
• Optimise for performance cost and reliability across environments devtestprod including capacity planning and operational SLAs
• Improve build and deployment automation for both platform services and Airflow DAGs versioning packaging promotions approvals
• Implement CICD best practices automated testing static analysis security scanning and controlled rollout rollback strategies
• Reduce manual toil by investing in self-service onboarding templates and engineering enablement tooling
• Implement end-to-end data lineage source platform vendor including metadata capture and a visual representation that supports auditability and faster incident resolution
• Enhance observability across pipelines and services logging metrics alerting and dashboards drive measurable improvements in MTTR and change failure rate
• Partner with product owners data owners architects vendors and governance teams to shape requirements and manage delivery expectations
• Lead agile ceremonies and engineering planning remove blockers and maintain delivery momentum
• Mentor engineers through code reviews design reviews and structured coaching foster a culture of continuous improvement

• Proven experience as a Technical Lead Engineer delivering data engineering or integration platforms in cloud environment
• Strong hands-on experience building production grade ETLELT pipelines and orchestration with Airflow
• Solid experience on Google Cloud Platform such as Data services eg BigQuery Cloud Storage PubSub Dataflow and or container platforms eg GKE Cloud Run IAM networking secrets management and environment separation
• Strong software engineering foundations Python APIs configuration management architecture design testing strategy and performance tuning

• You’d be joining an accredited Great Place to work for Wellbeing in 2024.
• To help support wellbeing we have trained ‘Mental Health Champions’ across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy.
• You will be empowered to explore, innovate, and progress. You will benefit from Capgemini’s ‘learning for life’ mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard Manage Mentor, Cybersecurity qualifications and much more.