Job location
Charing Cross, United Kingdom
Tech stack
Data analysis
Data Architecture
Data Mart
Data Transformation
Data Warehousing
Python
Metadata Standards
SQL Databases
Test Scripts
Software Version Control
Data Pipelines
Job description
so they have trust in the data for the types of decisions that they are making. Providing support as required when Data Engineers are building new data pipelines and ingesting data sources valuable to the wider business. Support data quality improvement, develop standards for data transformation and create and maintain appropriate documentation Refine requirements in response to feedback from users and changes in the organisation & provide ongoing support to users Utilise different approaches and techniques, whilst ensuring we apply industry-recognised data modelling patterns and standards. Work with team members to create, manage and maintain metadata standards, practices and tools. Design data architecture that deals with problems spanning different business areas, including maintaining & updating existing patterns or creating new, when necessary. Design test conditions, execute test scripts, and analyse and report on testing outputs and activities. Skills & Experience
Requirements
Essential Experience working as a data analyst, data engineer, or related role Excellent communication and stakeholder management skills Excellent SQL ability Understanding of data warehousing and modelling (particularly with data marts) Desirable Background in financial services AWS experience (particularly with Redshift) Good Python skills Experience with a form of version control Admiral: Where You Can We take pride in being a diverse and inclusive business. It's a place where you can Be You, and show up as you are. We're committed to fostering a people-first culture where everyone is accepted, supported, and empowered to be brilliant. You can, Grow And Progress at a pace and direction that suits you, Make A Difference for our customers and each other, and Share in Our Future with all colleagues eligible for up to £3,600 of free shares each year after one year of service. Everyone receives 33 days holiday (including bank holidays) when they join us
About the company
{"description": "We are recruiting for an Analytics Engineer to join our Tech & Data department at Admiral Money. The beating heart of Admiral Money is data, making this role an exciting opportunity to do work that has a meaningful impact on the core objectives of the business. In short: we believe data allows us to help grow the business, identify new opportunities and price and serve Our Customers appropriately. To enable this, we need to provide clean, tested, well-documented and well-modelled data, that will enable and empower all users. Your role as an Analytics Engineer would involve working closely with our Data Scientists, Data Analysts, and Business Users to surface the right data, in the right way, at the right time. About us Admiral Money is the dynamic lending arm of Admiral Group, offering personal loans, motor finance, and homeowner loans since 2017. We're building something special for our customers and are looking for curious, driven individuals ready to learn, take on
challenges, and make an impact. We're proud to be a certified Great Place to Work for over 25 years, with recognition for Women and Wellbeing. Our inclusive culture empowers everyone to Be You. Need support during the recruitment process? Just let us know - we're here to help. Responsibilities Perform a key role working with our experts across the business to understand how the data operates and supports a variety of business operations. Using your expertise, you'll model this out to most appropriately support this business to facilitate their modelling, analysis and reporting. Act as a data champion to the business, getting people excited by how data can support them to make better decisions and accelerating the success that these decisions drive. Keep usability and trust at the heart of all the models we provide. Any data marts and models will be well tested and well documented. We want to make it easy for people to know they're always using the right definitions and the right data