As a Data Analyst within an esteemed Asset Team, you'll play a pivotal role in maintaining and optimising operational efficiency in data collection services.
Join the ranks of a fast-growing, technology-based powerhouse, a true market leader revolutionising the energy data and services sector for over 40 years.
With a customer base exceeding 3.5k and a team of 300 dedicated professionals, we are on a mission to empower their clients to slash energy costs and carbon footprints.
We are recruiting for an Data Engineer within the Marketing group who will be responsible for leading and developing a range of projects and deliverables.
My client is is an international data and technology consultancy with £154m turnover and 1100 employees.
Role
You will be responsible for leading and developing a range of projects and deliverables including; audience insight through pen portrait and persona creation, new proposition development, pitching for new business, KPI and reporting dashboard creation and delivery.
Position: Data Analyst - Data Management & Compliance
We seek to recruit an individual who displays a flexible approach, excellent communication skills and is an effective team player
Benefits: 25 days' annual leave plus bank holidays (this will increase with service up to 30 days, full time equivalent) cashback and discount scheme, employee assistance programme, learning and development, pension scheme, Life Assurance, Eye Care vouchers, Long Service Award, Tax-free childcare, Health Cash Plan, Working Pattern Agreement, flexible working opportunities available.
The Data Engineer is a hands-on technical role responsible for designing, developing, and maintaining data pipelines within the IT department.
This role plays a crucial part in driving data-driven decision-making across the organisation, ensuring data availability, quality, and accessibility for various business needs.
The pipelines will be realised in a modern lake environment and the engineer will collaborate in cross-functional teams to gather requirements and develop the conceptual data models.