Data Engineering & Analytics Manager

Reporting to the General Manager of Data Engineering & Analytics, you'll manage several multi-disciplinary data delivery teams aligned to one of our key customer journey stages with a remit to deliver a wide variety of data analytics, and data integration initiatives.

As our Data Engineering & Analytics Manager, you'll have access to a wide range of benefits including:

Hybrid working (we're in the office 3 days per week)
Annual pay reviews
Colleague discounts on Jet2holidays and Jet2.com flights
What you'll be doing:

As an Data Engineering & Analytics Manager in our Data teams, you'll lead across 4 key areas: -

Data Delivery - You'll be responsible for the delivery performance of your teams and ensure key delivery metrics are closely monitored and allow you to best provide support where needed.
Data Culture - You'll drive a data-first culture both within the data team and across the business by supporting continual learning and development across your teams and the wider business
Data Architecture & Solution Design - You'll support the optimisation of our data architecture, working closely with other data managers and our data architecture team
Team Leadership - You'll manage several multi-disciplinary data delivery teams consisting of Data & Analytics Engineers and Test Engineers with Data Scientists and Data Visualisation specialists embedded as required.
What you'll have:

Communication and Management - Strong communication skills will be needed to influence teams and stakeholders at all levels of the organisation from Engineers to C-level. The role manages several multi-disciplinary teams, so you'll be experienced in setting direction and communicating priorities clearly
Analytical Focus - You should have practical experience helping business users to translate analytical requirements into technical solutions and ensuring that the right analytical questions are being asked
Technical Ability - Strong proficiency needed in designing and delivering data and analytics solution across multiple platforms as well as strong understanding of cloud platforms such as AWS, Azure and GCP (AWS is preferred). Desirable expertise in the following:
Data Warehousing - Snowflake (preferred), Google BigQuery, AWS Redshift or Azure Synapse. A good understanding, and practical experience, of analytical data modelling techniques is essential (e.g. dimensional modelling, data vault, etc)
Data Pipelines - Experience working with a wide variety of data sources and data transformation techniques
Data Visualisation - Although we have dedicated data visualisation specialists within the team, any knowledge of, or experience with, data visualisation platforms such as Tableau (preferred) would be beneficial
This role will likely be focused in our finance and corporate applications domain initially so although prior experience of working in a finance domain is not essential, any experience in this area would be a distinct advantage.

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