Senior Data Engineer

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