You’ll play a hybrid role bridging data engineering and data science, leveraging data from a broad range of sources (e.g. BigQuery, Redshift) and applying advanced analytics to generate actionable business insights. Using tools like Python, SQL, dbt, and visualization solutions, you’ll acquire, clean, and blend data, design robust ETL pipelines, and build models that drive Dyson’s decision-making.
You’ll partner directly with teams across the business to deliver practical recommendations, support high-impact analytics, and enable self-service solutions. As part of our innovative culture, you will stay ahead of industry trends, experiment with new methodologies, and shape how Dyson uses data.
Key ResponsibilitiesAcquire, cleanse, and blend data from multiple sources—internal and external—to enable advanced analytics.
Build and maintain scalable ETL processes and data models for dashboards, applications, and analytics projects.
Design, develop, and deploy machine learning models and statistical analyses to address business problems.
Support the BI function by powering dashboards, enabling self-service analytics, and managing business-facing applications.
Collaborate with data product managers and stakeholders to frame problems, gather requirements, and offer actionable recommendations.
Deliver end-to-end data solutions—from pipeline development and model training, to visualization and insight communication.
Regularly explore new technologies and approaches in data engineering and data science.
Minimum 5 years’ experience extracting, joining, and analyzing data, including supporting advanced analytics and modelling.
Logical, solution-oriented mindset—curious and driven to solve business and customer challenges.
Strong communicator, able to build compelling stories from complex or sparse data.
Proven ability to collaborate with local analytics teams, Group Data Function, and wider stakeholders.
Self-motivated with capacity to deliver practical results in short timeframes.
Degree in Computer Science, Data Science, Business Analytics, or a science/engineering field, or equivalent experience.
Strong Python skills for data manipulation, automation, and model development.
Comfort working with cloud-based platforms (e.g., BigQuery, Redshift); experience querying modern cloud databases.
Experience with dashboard tools (Tableau, Looker), and very strong Excel skills.
Hands-on experience in data cleansing, blending, and preparing data for modelling and analysis.
Track record building machine learning pipelines and working with statistical methods.
Experience building automated ETL pipelines, including deployment on cloud platforms.
Ability to explain complex data models and analytics to business audiences.
Finance or product costing analytics experience.
SAP data extraction know-how.
Experience hosting ETL pipelines on Google Cloud Platform tools.
dbt, Airflow, Docker experience.
App development (App Engine, PowerApps), advanced visualization techniques.
Familiarity with requirement gathering and solution design alongside end users.
This role empowers Dyson to use data and analytics to solve business challenges, speed up decision-making, and push the boundaries of innovation. You’ll help define—not just support—how Dyson finds and applies insight.
Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.
