.Oporto, PRT Hybrid Permanent Full Time 37.5 130519 Digital marketing is an essential function in helping to achieve the online sales performance and brand positioning for TUI. We are seeking an experienced Lead Data Engineer to join our digital apps team and take ownership of the design, development, and optimization of data pipelines and infrastructure on Google Cloud Platform (GCP). This is a key role where you will drive the technical architecture of our data engineering processes, ensuring scalability, performance, and alignment with the digital strategy of our applications. You will play a critical role in shaping the data landscape for our digital products, enabling product and analytics teams to harness data effectively for actionable insights. It is an exciting time to join TUI as we are accelerating our App transformation to a single platform across all markets. You will be working closely with other TUI source markets and stakeholders to establish and implement a common approach to App data management and practices within the Google cloud platform. Please note the closing date for applications is: Sunday 24th November ABOUT THE ROLE Lead the design, build, and maintenance of efficient and scalable ETL/ELT pipelines for digital applications using GCP tools such as BigQuery, Dataflow, Pub/Sub, Cloud Composer, and more. Ensure data ingestion from a variety of sources (e.G., web, mobile apps, third-party APIs) into Google Cloud, transforming raw data into ready-to-use formats for analytics and business intelligence. Own the architecture of data pipelines, ensuring optimal performance, cost-efficiency, and scalability on Google Cloud Platform (GCP). Implement best practices for data storage, query optimization, and performance tuning in BigQuery and related GCP services. Provide technical expertise to support digital app teams by creating data models, summary tables, and views that enable effective analysis and reporting. Work alongside App commercial and Product analysts and teams to understand their data needs, ensuring that pipelines and data models meet business requirements. Implement and maintain strong data governance policies, ensuring data accuracy, consistency, and security across all platforms. Ensure compliance with data privacy regulations (GDPR) and internal data handling guidelines, integrating privacy-by-design principles into the engineering process. Build automated workflows and solutions for data quality monitoring, pipeline execution, and reporting processes using tools like Python. Design and implement automation scripts for the deployment and scaling of data infrastructure, ensuring smooth and efficient data processing across the organization. Work closely with cross-functional teams, including product managers, data scientists, analysts, and marketing teams, to ensure data is easily accessible and usable for their specific use cases