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Data engineer

Longford (GL2 9)
hays-gcj-v4-pd-online
Data engineer
Posted: 17 December
Offer description

Role PurposeThe Data Engineer will design, build, and maintain robust data pipelines and architectures to enable AI-driven solutions for business, ensuring frameworks can scale across all OpCos. This role demands consultancy-level technical depthbined with a strong delivery discipline.
Contract – 6 months
Location – around Heathrow
Hybrid – 2 to 3 days onsite
Rate - Flexible day rate (inside IR35)

Key Responsibilities
1. Develop and optimize data pipelines for ingestion, transformation, and storage.
2. Ensure data quality, integrity, and security across systems.
3. Collaborate with Data Scientists and Analysts to enable advanced analytics.
4. Implement best practices for scalability and performance in cloud environments.
5. Support integration of MRO AI Solutions into business operational workflows.
6. Design data architecture and pipelines that support multi-OpCo deployment, ensuring modularity and interoperability.
Required Skills & Experience
7. Expertise in Python, SQL, and modern ETL frameworks.
8. Hands-on experience with cloud platforms (AWS preferred).
9. Strong knowledge of data modelling and API integration.
10. Proven experience in developing, testing, and deploying data solutions into production environments, ensuring reliability, scalability, and maintainability beyond proof-of-concept or prototype stages.
11. Familiarity with airline or logistics data domains is a plus.
12. Significant experience in similar roles, with a proven ability to integrate quickly into new teams and deliver immediate value.
13. Initial co-location with client’s teams in London is essential to ensure close collaboration. Candidates must also be prepared to travel internationally during later stages to facilitate group-wide deployment.
Preferred Consulting-Levelpetencies
14. Ability to design enterprise-grade data solutions under tight timelines.
15. Strong stakeholder engagement and solution-oriented mindset.
16. Experience in advisory or consulting roles for data engineering projects.
17. Track record of creating high-impact oues and driving stakeholder satisfaction from day one.
18. Ability to implement standards and frameworks for scalable data solutions across multiple operatingpanies.

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