WWF Overview
For 60 years, WWF has worked to help people and nature thrive. As one of the world’s leading conservation organizations, WWF works in more than 100 countries, connecting cutting-edge conservation science with the collective power of our partners in the field – with one million members in the United States and five million supporters globally, as well as partnerships with communities, companies, and governments.
At WWF, we are working to create an organization where the richness of all our unique views, experiences, and backgrounds combine to create the most sustainable and inclusive conservation outcomes possible, bringing the greatest benefit to the planet and every person who lives on it.
Across the many cultures and individuals that represent WWF, we are unified by one mission, one brand, and one common set of values: Courage, Respect, Integrity and Collaboration.
BRIDGE is WWF’s summer internship program. Launched in 2021, it is a paid internship opportunity aimed at a pool of talented undergraduate and graduate students who could bring fresh thinking and innovation to the environmental sector. In particular, WWF aims to employ interns who have not previously had a breadth of professional experience and have not previously considered conservation as a career pathway.
Position Summary
We are seeking a Data Engineer Undergraduate Intern for Summer 2025 to assist in developing and maintaining our growing data pipelines, integrating and ensuring the quality of data from a variety of sources. You will gain hands-on experience with industry-standard tools like Python, SQL, and cloud-based platforms, collaborating closely with data engineers and data scientists on real-world projects. This role includes structured mentorship, offering opportunities for continuous learning, professional growth, and the chance to make an immediate impact on our data infrastructure.
Internship Description:
Data Pipeline Development: Support the creation and maintenance of ETL pipelines, primarily using Python and SQL, to extract, transform, and load data from multiple sources. Data Integration: Help integrate batch data streams to ensure consistency, usability, and reliability. Data Quality Assurance: Contribute to data cleaning, validation, and documentation efforts to ensure high data quality and integrity. Infrastructure Support: Assist in optimizing and scaling our data infrastructure, working with Azure/MS Fabric platforms and containerization tools. Collaboration: Participate in team stand-ups and kanban planning, working alongside data engineers, data scientists, and stakeholders to fulfill data requirements. Learning & Development: Engage in continuous learning through mentorship sessions and self-paced resources to develop new technical skills and stay current on best practices.
Minimum Requirements:
Pursuing an associate’s or bachelor’s program in Computer Science, Data Science, Engineering, or a related field. Those studying outside these areas are still highly encouraged to apply. Must be an actively enrolled student and not received degree at time of internship start date (June 16, 2025). Technical Skills: Basic proficiency in Python and SQL. Data Management: Familiarity with database management systems and ETL concepts. Identifies and aligns with WWF’s core values: Courage, Integrity, Respect, and Collaboration. Demonstrates courage by speaking up even when it is difficult, or unpopular. Builds trust with colleagues by acting with integrity, owning mistakes, and holding oneself accountable. Welcomes other points of view and ideas, recognizing and embracing different and contrary perspectives with kindness, curiosity, and encouragement. Makes conscious efforts to promote cooperative practices, behaviors, and ways of working across many groups and individuals.
Preferred Qualifications:
Subject expertise in one or more of the following areas is preferred, but not required:
Technical Skills: Exposure to data warehousing solutions (e.g., Azure Synapse). Problem-Solving: Strong analytical mindset and eagerness to tackle complex data challenges. Communication: Solid written and verbal communication skills for effective collaboration and documentation.