**Who You'll Work With**: You will be based in one of our LatAm offices as part of McKinsey Digital. McKinsey Digital brings together the best of McKinsey’s digital capabilities to help our clients use digital technology to transform their businesses. As part of this group, you’ll join a global team working on everything from IT modernization and strategy to agile, cloud, cybersecurity and digital transformation. You’ll typically work on projects across all industries and functions and will be fully integrated with the rest of our global firm. You’ll also work with colleagues from across McKinsey & Company to help our clients deliver breakthrough products, experiences and businesses, both on technology and non-technology topics. Our office culture is casual, fun and social with an emphasis on education and innovation. We have the freedom to try new ideas, experiment and are expected to be constantly learning and growing. There is also a strong emphasis on mentoring others in the group, enabling them to grow and learn. **What You'll Do**: You will work in multi-disciplinary environments harnessing data to provide real-world impact for organizations globally. In this role, you will build innovative technologies that lay the foundations for our Data Science solutions at scale. You will implement new and ongoing data integration needs to complete end to end deployment of our solutions. You will support development and implementation of products, working in collaboration with stakeholders and team members to analyze user needs, develop data integration solutions and help with continuous evolution of product architecture. You will also manage data including definition, usage, and quality via suitable repositories and artefacts like data dictionary, data models, metadata and data quality logs. Lastly, you will conduct data assessment, perform data quality checks, transform and load raw data. **Qualifications**: - Undergraduate degree in computer science, engineering, mathematics or related field - 0+ years of experience - Knowledge of software engineering concepts and best practices - Knowledge building data pipelines in production and ability to work across structured, semi-structured and unstructured data - Understanding of data modelling, data lake concepts and Tableau dashboards, visualizations, etc. - Ability to write clean, maintainable, and robust code in Python and SQL; familiarity with Java and Scala is a plus - Knowledge in facets of software development life cycle like analysis, design, development, data conversion, data security, system integration and implementation