Job title: Senior Data Engineer Will the role be 100% remote, hybrid or 100% office? Hybrid – 3 days/week If the role is hybrid/ office based specify location: London, UK Duration of assignment: 6 months contract InsideIR35 Role description: Join a high-impact data transformation programmed within the aviation sector, where a global leading airline is undergoing a major data modernization journey. The initiative goes far beyond a basic lift and shift; it’s a forward-looking transformation that blends the stability of mature legacy systems with the innovation of cloud-first, AI-driven architecture. As a senior data engineer, you’ll play a critical role in building and optimizing modern, scalable data solutions that enable smarter decision-making, richer customer experiences and operational excellence. You’ll be a part of a highly collaborative network of teams working with cutting edge cloud-based technologies whilst also navigating complex legacy ‘on-premises’ environments. This role offers engineers the opportunity to leave behind traditional approaches and contribute to a programmed with long-term impact at the forefront of aviation data innovation. Key responsibilities: Design, build and maintain robust data pipelines that support critical business applications and analytics Analyze, re-engineer and modernize existing ETL processes from legacy systems into scalable cloud-native solutions Contribute to the development and optimization of a cloud-based data platform, leveraging tools like snowflake, AWS and airflow Work closely with data architects, analysts and other engineers to deliver high-quality, production-ready code Participate in code reviews, ensuring adherence to best practices and high engineering standards Investigate data quality issues and implement monitoring and alterting systems to ensure pipeline reliability Document workflows, data lineage and technical designs to support maintainability and knowledge sharing Champion a culture of continuous improvement, experimentation and technical excellence within the team Key skills/knowledge/experience: Strong hands-on experience with data engineering in both on-prem and cloud-based environments Good working knowledge and hands on experience working with Teradata and Infomatica. Proficiency in working with legacy systems and traditional ETL workflows Solid experience building data pipelines using modern tools (Airflow, DBT, Glue etc.) and working with large volumes of structures and semi-structured data Demonstrated experience with SQL and Python for data manipulation, pipeline development and workflow orchestration Strong grasp of data modelling, data warehousing concepts and performance optimization techniques Hands-on exposure to cloud platforms, especially AWS Experience working in agile teams and using version control and CI/CD practices Desirable skills/knowledge/experience: Experience with Snowflake or other cloud-native data warehouse technologies Familiarity with GraphQL and its use in data-driven APIs Exposure to data governance, data quality and metadata management tools Interest or experience in applying machine learning / AI pipelines or features within a data engineering context Understanding of DevOps conceps as applied to data (DataOps) and infrastructure-as-code tools like Teraform or Cloudformation Previous experience in highly regulated industries or large-scale, enterprise-grade environments