Mentoring students in analytics engineering, dbt, and the modern data stack, providing hands-on learning experiences to help them build practical skills in data modeling, transformation, and pipeline development.

SQL, dbt, BigQuery, PostgreSQL, and Github.

Currently building a scalable data platform for Dunelm to unify and process data, enabling better decision-making.

SQL, Python, Terraform, dbt, Snowflake, AWS, and GitHub.

Contributed to the rebranding of core features for FanDuel Racing's desktop and mobile products, ensuring a modern and consistent user experience across platforms.

- Collaborated on the development of scalable front-end solutions, enhancing the platform's usability and visual appeal.

- Supported the creation and management of reusable components and content structures to streamline development workflows.

React, React Native, NextJS, Typescript, Javascript, GraphQL, Styled Components, Storybook, Storyblok, and GitHub.

Contributed to the development of an ELT pipeline that unified Dunelm's operational and sales data, enabling data-driven decision-making and shaping the company's business strategies.

- Assisted in building a Data Lake to centralize all operational and sales data.

- Promoted Data Warehouse modeling using Kimball's methodologies to enhance analytical capabilities.

- Conducted exploratory data analysis to understand business processes and translate them into well-structured data models.

- Advocated for a design-quality mindset by introducing Test-Driven Development (TDD) techniques for data model development.

- Played a key role in implementing continuous integration/continuous deployment (CI/CD) pipelines to ensure a high-quality, reliable data system.

SQL, Python, Bash, dbt, Snowflake, AWS, Terraform, and GitLab.

Contributed to the development of a robust ETL pipeline to unify data across BMW's systems, enabling data-driven decision-making and empowering the organization to adopt a data-centric approach.

- Played a key role in building and maintaining the infrastructure for scalable and efficient data pipelines.

- Ensured high-quality data models through rigorous testing and optimization practices.

SQL, Python, Terraform, Apache Spark/PySpark, AWS, and Bitbucket.