The Role
Join a high-impact data transformation program 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 experience 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 program with long-term impact at the forefront of aviation data innovation.
Your 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, GitHub and airflow
Experience in migrating data from legacy platforms, such as Teradata, to modern cloud- based data platforms like Snowflake would be highly advantageous.
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 alerting 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.
Essential 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 Informatica.
Proficiency in working with legacy systems and traditional ETL workflows
Solid experience building data pipelines using modern tools (Airflow, DBT, GitHub, 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 cloud-native data warehouse technologies with Unix, Control-M, Airflow, Python, AWS.
Exposure to data governance, data quality and metadata management tools.
Experience in building the features for Data science team within a data engineering context.
Understanding of DevOps concept as applied to data (DataOps) and infrastructure-as-code tools like Terraform or CloudFormation
Previous experience in highly regulated industries or large-scale, enterprise-grade environments and good to have the exposure to the Aviation Industry.