Cube RM is the leading global Tender Software company, empowering Life Sciences organisations to find more business opportunities with the power of Data and AI. Our platforms use the latest technology to capture key tender market data globally and transform it into actionable market intelligence, coupled with seamless software automation and industry expertise to increase tender processes efficiency.

To further drive the provision of smart solutions and ensure effective utilisation of the vast amount of data collected, analysed, processed and delivered as data products, we are looking for a driven data practitioner at the intersection of data analysis and data engineering to join our team. With a knack for providing tech solutions, passionate about data and developing value-adding analytical output. Eager to ensure proper data pipelines and performance, ready to make suggestions and take action to boost execution and delivery.

As an Analytics Engineer at Cube RM, you will have the opportunity to engage with multiple parts of the data journey towards meeting and exceeding the expectations of world-class companies. Work collaboratively in a fast-paced, high-growth environment to continuously improve insights and intelligence offerings through the SaaS platforms of Cube RM using state of the art software technologies.

If you think you would be a fit for this role and innovation is your game, we would love to hear from you. Join our dynamic team in driving transformative growth in the Life Sciences industry!

Responsibilities

• Work closely with Data practitioners to take data analysis on public tender data to the market through robust and production-ready platforms
• Further enable the application of analytical tools and modeling techniques, derive insights, build products in sync with tech teams
• Collaborate with product and customer-facing teams to understand requirements and streamline the execution and provision of data deliverables to clients
• Actively participate in identifying and addressing data quality issues, anomalies, missing values, and inconsistencies in core datasets with an aim to improve overall data quality
• Extract, transform, and load public tender data from various sources into databases, analytical platforms
• Optimise associated ETL processes, ensure observability, monitoring and automation of data-driven workflows
• Actively participate in the development of interactive visualisations and client-facing dashboards