Data Analyst

The Data Analyst will work with clients to design and deliver analytical solutions that help solve business problems and drive data-informed decision-making. This role offers the opportunity to work across a wide range of analytical tasks for our production clients, enabling them to fully leverage the data we capture to improve operational efficiency, support the development of new analytical solutions, and address key business challenges., * Analyse and interpret procurement and commercial data to generate actionable insights and support strategic decision-making.

• Collaborate closely with multidisciplinary teams worldwide, client managers, and key stakeholders to deliver high-quality analytical outputs to clients.
• Contribute to the delivery of end-to-end analytical projects and solutions, with guidance and support from senior team members.
• Track, manage, and help resolve project risks, issues, and action items throughout the project lifecycle.
• Ensure the quality, accuracy, and consistency of analytical deliverables through robust cleansing, transformation and validation practices.
• Manage priorities effectively to meet project deadlines in a fast-paced environment.
• Work with client teams and senior members of DSA to develop clear, client-ready presentations, both technical and non-technical.
• Support data validation, cleansing, and transformation activities to ensure high data quality.
• Identify opportunities to improve analytical processes, automation, and reporting efficiency.
• Ensure all work is properly documented.

• Strong programming skills in SQL; experience with Python is a plus.
• Experience in commonly used database platforms: MySQL, Amazon Redshift, Snowflake.
• Good data mining, data manipulation, and analytical techniques.
• Strong attention to detail and highly accurate work.
• Excellent communication skills, both written and verbal.
• Self-starter with proactive attitude and enthusiasm for data. Able to collaborate in a team environment and work independently.
• Able to prioritise tasks and manage expectations for own work.
• Eagerness to learn and a proactive “can-do” approach.
• A degree or equivalent in a numerical, analytical, or technical subject (e.g., Mathematics, Statistics, Computer Science, Economics)., * Familiarity with DBT, data pipelines, and cloud environments, supporting the development of efficient and scalable data workflows.
• Low-code or no-code tool knowledge (e.g., Retool).
• Experience using version control tools such as Git, GitHub, or SVN.
• Familiarity with agile ways of working in a team environment.