Data and AI Graduate

Job Description Start your career at Sage in a role focused on artificial intelligence, data engineering and responsible innovation. You will build practical experience in how trusted data powers AI, how scalable data platforms support better decisions, and how emerging technology can be applied safely and effectively across a global software business. Why join Sage as a graduate? As a graduate, you will be supported with structured learning, access to mentors and subject matter experts, and opportunities to work with teams across Sage. You will develop technical confidence, commercial understanding, and communication skills needed to turn data and AI ideas into useful outcomes. You will also have access to Sage Foundation, which gives colleagues five paid volunteer days each year, alongside development time and a wider graduate network. Key Responsibilities What will you be involved in? The Data \& AI Graduate Programme is designed to give you broad, practical experience in how AI solutions are shaped, governed, and supported by strong data foundations. You will learn how high quality data, clear problem framing, responsible AI principles, and scalable engineering practices come together to solve real business challenges. As part of your rotations, you could work with teams such as the Data Hub, gaining exposure to modern cloud and streaming technologies. This may include tools and approaches such as Snowflake, AWS services, Kafka, Flink, Apache Iceberg, Apache Spark and DBT, depending on the team and project needs. * Help build robust, scalable data pipelines that support real-time and batch data processing. * Support data products that provide curated datasets for analytics, machine learning, and AI use cases. * Contribute to work linked to predictive analytics, recommendation systems, anomaly detection, and intelligent automation. * Learn how feature stores, model training pipelines and data governance frameworks support scalable and secure AI and machine learning activity. * Explore how AI and automation can improve reporting, analysis, productivity, and decision making. * Support work that improves data quality, consistency, definitions, and trust across the organisation. * Work with technical and non technical colleagues to frame problems, gather requirements, and share progress clearly. What you will build * A strong understanding of how AI depends on trusted, well managed, and accessible data. * Practical experience using data, analytics, cloud, and AI tools to support business decisions. * An understanding of how data engineering supports AI, machine learning, and advanced analytics. * Confidence in responsible AI, including governance, accuracy, privacy, security and risk awareness. * The ability to explain technical topics clearly to different audiences. * A foundation for a long-term career in AI, data engineering, analytics, governance, or insight. Example responsibilities * Assist in building and maintaining data pipelines using tools such as Apache Spark, AWS Glue and Kafka. * Support the development and optimisation of data lake and warehouse solutions using platforms such as Snowflake and Iceberg tables. * Work with senior engineers to ingest, transform, and model data for analytics and machine learning use cases. * Take part in the deployment and monitoring of data workflows in AWS cloud environments. * Help improve data quality, reliability, and performance across systems. * Document processes and contribute to knowledge sharing within the team. What we are looking for To be eligible for this role, you will need a degree with a strong analytical, technical, numerical, or problem solving focus. This could include Computer Science, Software Engineering, Data Science, Mathematics, or a related subject. We are also looking for: * A strong interest in AI, data engineering and how technology can be used responsibly in business. * Curiosity about data platforms, automation, analytics and continuous improvement. * Familiarity with SQL and Python or TypeScript. * An understanding of cloud platforms, ideally AWS. * Exposure to data engineering concepts such as ETL or ELT, data lakes and data warehousing. * Interest in streaming technologies such as Kafka and batch processing frameworks such as Spark. * A self-starting approach and openness to learning in a changing environment. * Clear communication skills and the ability to work with colleagues across different teams and locations. * Good judgement, attention to detail, and the willingness to check the quality and context of AI generated outputs. What you can expect from the process * Apply online with your CV. * Complete screening and a video interview. You will receive a link to complete the video interview within one week of applying. * If successful at video interview stage, you will be invited to attend an assessment centre. * Successful candidates will join us in October 2026. Inclusive hiring We are committed to inclusivity for all. If any adjustments would help you perform at your best during the application process or beyond, please contact earlycareers@sage.com. Please note that due to the high volume of applications, there may be a delay in receiving a response from your video interview. Thank you for your patience. Benefits of working at Sage include * 25 days holiday plus bank holidays from day one * Paid time to learn, with 5 learning days a year * Paid time to give back, with 5 volunteering days a year * Private healthcare, digital GP, and wellbeing support * Competitive pension with Sage contributions * Paid parental leave, inclusive from day one * Work from abroad for up to 10 weeks a year * Discounts on tech, travel, gyms, and more * Cycle to Work and EV schemes