Intermediate Data Engineer (with GCP)

ENVIRONMENT:

A technology-led company operating within the travel domain is seeking a hands-on Intermediate Data Engineer to take full ownership of and optimise its end-to-end data engineering capability. Working as the sole data engineering specialist within a small, agile team, you will design, build, and maintain scalable, high-quality data pipelines that support business intelligence, advanced performance analytics, machine learning, and other AI-driven initiatives across cloud platforms.  This role requires responsibility for ensuring exceptional data quality, reliability, and usability across the organisation. The ideal candidate brings strong problem-solving ability, the confidence to challenge existing approaches, meticulous attention to detail, and the ability to work both independently and collaboratively. A delivery-focused mindset, coupled with genuine curiosity and a desire to continuously learn and add value, is essential.

 

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.

---