Business Data Steward - FTC
Listed on 2025-12-30
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IT/Tech
Data Analyst, Data Engineer
Business Data Steward (12 month FTC) – Luton/Hybrid
When it comes to innovation and achievement there are few organisations with a better track record. Join us and you’ll be able to play a big part in the success of our highly successful, fast-paced business that opens up Europe so people can exercise their get-up-and-go. With almost 300 aircraft flying over 1,000 routes to more than 32 countries, we’re the UK’s largest airline, the fourth largest in Europe and the tenth largest in the world.
Set to fly more than 90 million passengers this year, we employ over 10,000 people. It’s big-scale stuff and we’re still growing.
The Business Data Steward is a pivotal role essential for developing and supporting domain business requirements for data acquisition and management. maintaining high-quality, reliable data within a specific business domain while aligning it with business objectives. This is a role within the central data team that works closely with business leaders and technical teams across various business functions to ensure data quality, as well as to make our data discoverable, accessible, and effectively used both within the domain and across the organization.
JOBACCOUNTABILITIES
- Communication:
Excellent communication skills, capable of explaining complex technical concepts to non-technical stakeholders and at CxO level. - Problem Solving:
Strong analytical and problem-solving abilities, with a proactive approach to identifying and resolving data quality issues and supporting business data domains to scale data quality management and remediation. - Requirements Elicitation. Collect, document, and clarify the requirements and conditions essential for a project or initiative, ensuring they are comprehensive, precise, and aligned with the business objectives.
- Collaboration. Ability to work effectively with cross-functional teams and manage relationships with various stakeholders.
- Attention to detail. Precision and attention to detail to ensure the accuracy and completeness of data.
Deep understanding of:
- Relevant data protection laws and regulations, such as GDPR
- Data management frameworks for each of the data management capabilities (data quality, reference data management and metadata management)
- Data management tools (data quality, reference data management and metadata management) and experience working with them
- Data ownership and stewardship models
- Delivery focused, the definition of done is focused on adding and delivering value by leveraging reusable data assets and products, making them discoverable by the business to drive value and differentiation in the marketplace.
- Extensive experience in data governance and management and the interaction across different data disciplines to bind their ways-of-working together results in a consistent and repeatable process for high-quality data delivery on the eJDP.
- Conceptual & Logical Data Modelling concepts are fully understood, as well as the application of the technique to domain modelling for product development and the design of relational, dimensional and data vault based data structures for modern data platforms.
- Programme Management is critical for understanding business domain roadmaps and ensuring the successful alignment of data governance initiatives with business priorities to ensure assets under governance support and enhance business goals.
- Knowledge of Agile development methodologies and interaction of data governance within Data Ops.
- Proficiency in using data governance tools and platforms to automate and optimise data management steps and gateways into data and analytical pipelines.
- Expertise in implementing and managing statistical process controls for data quality measurement, continuous observability, and data quality remediation.
- Strong SQL background – comfortable writing efficient SQL (Transact-SQL, Hive
-HQL) to meet the requirement, having had exposure to working with large datasets on a distributed data platform environment
- Knowledge of delivery techniques e.g. SCRUM, Agile & Waterfall
- Data Management principles – tagging, access management, data privacy, handling of sensitive…
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