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. Our priority is the delivery of high-quality, well-modelled, clean, and trustworthy data assets for use across the business. Our data teams also work hard to support all our data assets and ensure the business realise maximum benefit and return on investment from them.

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 flights

What you'll be doing:

As a 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. You'll look for continuous improvement in our data delivery process and take an active role in larger more complex data initiatives from design through to deployment.
• 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 to ensure we have a good understanding of emerging trends in data landscapes, technology solutions and consider them as part of our longer-term data strategy.
• 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. The data teams are expanding rapidly, and you will play a key role in recruitment across your teams and support the ongoing learning and development of your team members.

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.
• Technical Ability - Strong proficiency in writing and understandingSQL queries across multiple platforms with a strong understanding of cloud platforms such asAWS, Azure andGCP (AWS is preferred). Desirable but not essential 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 Pipeline - Experience working with a wide variety of data sources and data transformation techniques. Any experience with dBt would be an advantage as would experience using Python to build customer transformation logic.
  • CI/CD & Automation - We rely heavily on Infrastructure as Code for cloud infrastructure deployment so any experience with technology such as Terraform would be beneficial in this respect.
  • 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), Power BI, Looker or Quicksight would be beneficial.
• Analytical Focus - You should have practical experience helping business users translate analytical requirements into technical solutions and ensuring that the right analytical questions are being asked. You should have experience working in a collaborative environment with multi-disciplinary teams of data and analytics professionals to solve business problems effectively. A good understanding of data analysis and analytical techniques would be an advantage in this role.

This role will likely be focused on our finance 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. From a data analytics perspective this would involve ingesting data from our Microsoft Dynamics 365 finance system, supporting self-service reporting requirements on this platform, delivering data integration and analytics initiatives on finance data, and ensuring appropriate governance and controls are in place on our key financial reporting data pipelines.