Senior Data Analyst / Data Engineer

We're hiring a senior, hands-on Senior Data Analyst / Data Engineer to support the delivery of AI-enabled, decision-support solutions within a large, complex operational environment, with designs that scale across multiple operating companies.

This role sits across advanced analytics and data engineering, with work flexing depending on the delivery phase and workstream. You will operate as a senior individual contributor, embedded within a cross-functional product squad alongside Data Scientists, Visualisation Engineers, and change teams. The role is highly hands-on and delivery-focused, suited to someone who enjoys deep problem-solving, data exploration and building production-ready analytical assets.

Please note this role operates in a hybrid model with candidates expected to be able and willing to work from our customer's London office three times per week.

Required Experience:

7+ years experience in data analysis, analytics engineering or data engineering within a product or delivery-focused environment

Advanced skills in SQL and data processing using Python (e.g. Pandas)

Hands-on experience developing and optimising data pipelines for analytics and reporting use cases

Experience working with data visualisation tools such as PowerBI, Tableau, or similar

Proven ability to understand, assess and modernise legacy datasets and pipelines

Strong understanding of data modelling and API integration

Experience developing, testing and deploying production data solutions (not just PoCs)

Familiarity with cloud platforms (AWS preferred) and working knowledge of DevOps concepts (CI/CD, version control)

Comfortable working independently and communicating with non-technical stakeholders

Strong stakeholder engagement and solution-oriented mindset

Ability to deliver high-impact outcomes under tight timelines

Experience working in advisory or consultancy-style delivery settings

Key responsibilities & duties include:

Discover, connect to, and analyse data from a wide range of sources, including relational databases and flat files (CSV, YML, XLS etc.)

Identify, investigate and remediate data quality, completeness, and consistency issues

Challenge data provenance, assumptions and definitions within legacy datasets to ensure they are fit for modern analytics and AI use cases

Translate business questions into clear analytical approaches, KPIs, metrics and data narratives

Support the definition of KPIs and analytical logic that underpin dashboards and operational reporting

Design, develop, and optimise data pipelines for ingestion, transformation, and storage

Ensure data pipelines are production-ready, reliable, scalable, and maintainable beyond proof-of-concept

Implement best practices for data quality, integrity, security, performance and scalability in cloud environments

Support multi-OpCo deployment by designing modular, interoperable data architectures and pipelines

Collaborate with Data Scientists to prepare, validate, and structure datasets that support advanced analytics and AI-driven solutions

Support the integration of analytics and AI outputs into live operational workflows, ensuring outputs are actionable and adopted

Willingness to travel internationally during later stages to support group-wide deployment

Desirable Experience:

Familiarity with airline or logistics data domains

Ability to implement standards and frameworks for scalable data solutions across multiple operating companies