2 of 2 Remote Data Visualisation Jobs in Nottingham

Company Description Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions … Ireland. Learn more at experianplc.com. Job Description Internal Grade D The mission of the Business Intelligence function is to become the center of excellence across Service, providing trusted data and insights to our partners in a simple way. We want to set the bar for what great is whilst ensuring efficiencies are optimised. You will be the contact … sources Experience developing sustainable, insightful, automated OI/BI Experienced with data ETL (Azure Data Factory, AWS Glu, Postman, SSIS), manipulation and data visualisation tools (Power BI/Tableau) Hands-on experience data warehousing (DBA) design and principles An understanding of forecasting principles and main contact centre metrics Partner management experience More ❯

Job Title: Data Engineer Location: Hybrid Contract Type: Permanent/Full-Time About the Role Are you passionate about technology and eager to make a real impact? At Buzz Bingo, we’re looking for a Data Engineer who thrives on innovation and enjoys working across a diverse technology stack. The systems you’ll support underpin both … our in-club and online customer experiences, giving you the opportunity to influence how thousands of people interact with Buzz Bingo every day. What You’ll Do Data Pipeline Development: Design, implement, and maintain robust ETL/ELT pipelines for ingesting and transforming data from multiple sources. Data Modelling: Create and maintain models that … support analytics and reporting needs, ensuring data integrity and consistency. Database Management: Administer and optimize relational databases for efficient storage and retrieval of large datasets. Collaboration: Work closely with software engineers, analysts, and business teams to deliver secure, reusable, and efficient data solutions. Data Quality Assurance: Implement checks and monitoring processes to ensure accuracy More ❯