Overview ENVIRONMENT: A Cape Town Travel Tech company that focuses on the global supply and revenue optimisation of travel ancillary products and services is looking for a hands-on Intermediate Data Engineer to take ownership of and optimise their entire data engineering function. As the sole data engineering expert in a small team, you'll design, build, and maintain robust data pipelines that power business intelligence, advanced performance analytics, machine learning & other AI-driven initiatives – using GCP and AWS. You are responsible for ensuring that their data quality and density is of the highest standard. The role demands creative problem-solving, courage to challenge the status quo, meticulous attention to detail, the ability to work independently and collaboratively, a delivery-mindset and a deep hunger to learn and contribute. Duties Manage, monitor, and optimise BI and data infrastructure costs across GCP and related tools. Lead end-to-end data pipeline development, including ingestion, transformation, and delivery of structured and unstructured data for reporting. Design and maintain data models (semantic model) and warehousing solutions to ensure accuracy, reliability, and usability for downstream consumers. Monitor pipeline performance, troubleshoot issues, and implement data quality controls, cleansing, and alerting processes. Partner with Product, BI, Engineering, and Operations teams to provide data for AI/ML initiatives, system monitoring, customer analytics, and performance dashboards. Automate recurring data processes to improve efficiency and reduce manual work. Document data processes and support knowledge sharing; contribute to technical roadmaps and overall data strategy. Stay informed on fintech and data-engineering trends to proactively enhance the data ecosystem. Own and resolve data-related issues, queries, and support requests. Identify opportunities for new data insights and recommend strategies that add value for internal and external stakeholders. Identify and operationalise new data sources that support analytics and system performance monitoring. Manage Google Analytics and Google Tag Manager to ensure accurate event tracking and reporting for web applications. Own and prioritise the data backlog, managing stakeholder expectations and distinguishing critical needs from nice-to-haves. Act as backup for the BI Developer when required. Contribute to future development and deployment of machine-learning models to support data-driven decision-making. Requirements Minimum Requirements: Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, Information Systems, or related field. 3+ years as Data Engineer or similar, owning full data pipelines in fintech or high-scale environments. Strong data warehousing, integration, quality, and governance practices. Advanced SQL skills including performance optimisation and working with large datasets. Proficient in Python, GCP (BigQuery, storage buckets), and CI/CD via GitHub. Experience ingesting from GTM/GA and AWS for analytics pipelines. Preferred PowerBI and Google Looker Studio for visualisations Machine learning model integration/deployment Familiar with Agile Scrum Framework, Jira and Confluence Attributes Excellent problem-solving skills and ability to work independently to meet project deadlines. Thrives in a small team setting and takes ownership. Self-motivated, with excellent communication skills for cross-functional collaboration. Passionate about the power of data and its ability to unlock tangible business value. #J-18808-Ljbffr