Role Description We are looking for a forward-thinking Data Engineering Intern to join our team for Summer 2026. This isn't just a role about moving data from point A to point B; it’s about rethinking how those pipelines are built. You will sit at the intersection of core infrastructure and AI, building robust ETL processes while leveraging AI technologies to automate the very workflows you create. Your mission is dual-purpose: you will support our Business Intelligence efforts and directly influence our product roadmap by turning raw data into actionable insights through advanced dashboards and automated workflows. A Day in the Life - Build & Orchestrate: Design, develop, and maintain ETL pipelines to ingest data into our Snowflake warehouse using Python, SQL, and Airflow. - AI-Driven Automation: Implement AI-powered solutions to streamline engineering tasks, including: - Automating code generation and documentation. - Building AI-driven data quality checks and anomaly detection. - Developing "self-healing" pipelines that can identify and alert on ingestion errors. - Insight Generation: Use Jupyter Notebooks and Streamlit to analyze data and build internal tools that help our product team make data-driven decisions. - Visualization: Create high-impact dashboards in Tableau that translate complex data into a clear narrative for stakeholders. - Agile Collaboration: Participate in daily Scrum huddles, manage tasks via Jira, and work closely with product owners and QA to promote code to production. - Cloud Infrastructure: Interact with cloud services via CLI and manage containerized environments using Docker and Kubernetes. Qualifications - Currently pursuing an undergraduate degree with a targeted graduation date in 2026 or early 2027, or pursuing a degree in Computer Science, Data Science, or a related quantitative field. - Expertise in Python and SQL. - A strong understanding of Data Warehousing (Snowflake) and ETL orchestration (Airflow). - Familiarity with CLI, Docker, and Kubernetes for managing cloud-based environments. - Experience with Jupyter Notebooks, Tableau, or Streamlit. - A proactive approach to using AI/LLMs to automate repetitive tasks and improve system reliability. Requirements - By the end of your 10-week internship, you will have designed and deployed a functional ETL pipeline that feeds into a custom Insights Dashboard. - Your work won't just sit in a folder; it will be used to influence our official product roadmap. Interview Process - Recruiter Phone Screen - Technical Assessment - Hiring Manager Interview - Team Interview Benefits - Remote, but you must be located in CA, AZ, CO, NC, or UT during the internship. - Duration: June 8, 2026 - August 14, 2026, working 40 hours per week. - Compensation per hour by location: - San Francisco Bay Area, CA: $50.00 - California (outside of San Francisco Bay Area): $46.25 - Colorado: $42.50 - Utah, Arizona, and North Carolina: $40.00 - Actual compensation packages are determined by various factors unique to each candidate, including but not limited to skill set, depth of experience, certifications, specific work location, and performance during the interview process. - In addition to base salary, this role may include variable compensation and be eligible for an equity grant, depending on the position and level. - Base salary range: $40 — $50 USD.

• Help define company data assets (data model) • Help define and design data integrations, data quality frameworks and design and evaluate open source/vendor tools for data lineage • Work closely with Dropbox business units and engineering teams to develop strategy for long term Data Platform architecture to be efficient, reliable and scalable • Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems • Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way • Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains • Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts

• Desarrollar pipelines de datos utilizando Databricks para procesamiento y transformación de grandes volúmenes de información. • Construir y optimizar consultas a bases de datos (SQL) asegurando eficiencia y escalabilidad. • Diseñar modelos de datos orientados a analítica y reporting. • Desarrollar dashboards y reportes en Power BI, integrando fuentes de datos diversas. • Implementar soluciones para análisis de customer journey analytics, asegurando trazabilidad y consistencia de datos a lo largo del ciclo del cliente. • Integrar múltiples fuentes de datos (internas y externas) para generar datasets confiables. • Automatizar procesos de carga, transformación y actualización de datos (ETL/ELT). • Trabajar en conjunto con equipos de negocio para traducir requerimientos en soluciones técnicas. • Asegurar buenas prácticas de desarrollo (versionamiento, documentación, testing).

Role Description You are the engine that turns complex data strategies into high-performing reality. As our Data Cloud Developer, you won’t just execute tasks; you’ll build the technical foundation that allows our clients to finally see a 360-degree view of their customers. We need your hands-on expertise to bridge the gap between architectural blueprints and live, scalable solutions that drive massive business impact. Qualifications - 5+ years of proven success in Salesforce development and implementation, with a deep technical focus on Salesforce Data Cloud. - Hands-on mastery of data modeling within the Salesforce ecosystem, including DMO/DLO mapping and identity resolution rulesets. - Technical proficiency in SQL and Data Ingestion, with experience connecting Data Cloud to external platforms like Snowflake, BigQuery, or Amazon S3. - Strong command of Salesforce automation, specifically using Flow and Apex to trigger actions based on unified profile changes. - A track record of technical problem-solving, with the ability to debug complex data streams and transformation logic independently. - Relevant certifications, such as Salesforce Data Cloud Consultant or Salesforce Strategy Designer, paired with a solid understanding of the Data Cloud lifecycle. Requirements - Build and configure end-to-end Data Cloud solutions, from initial data-stream ingestion to final activation of segments. - Transform raw data into actionable insights by writing calculated insights and mapping complex data schemas with precision. - Collaborate closely with Architects to translate high-level solution designs into functional technical requirements and clean code. - Own the technical health of the platform, ensuring data refreshes are seamless and identity resolution is performing at its peak. - Develop powerful activations that push unified data to Marketing Cloud, Sales Cloud, or external endpoints to trigger real-time customer journeys. - Stay ahead of the curve by experimenting with the latest Data Cloud releases (like Data Spaces or AI-driven features) to keep our clients at the cutting edge. Benefits - Successfully integrated into assigned client projects and are consistently hitting your billable targets. - Execute technical builds for Data Cloud implementations, ensuring 100% data accuracy and seamless system integration. - Become a "go-to" technical expert for complex Data Cloud troubleshooting, recognized for your ability to turn messy data into a unified, high-value asset.