• Collect, process, and load data from diverse sources • Elicit requirements from stakeholders • Develop integrations between different platforms • Create and improve Business Intelligence platforms • Ensure delivery quality through rigorous reviews

• Develop data solutions using Python, ensuring quality, performance, and scalability; • Develop and maintain REST APIs for integration between systems and applications; • Build, optimize, and maintain ETL/ELT data pipelines; • Process and transform large volumes of data using Apache Spark and PySpark; • Develop queries and analyses using SQL to support decision-making; • Participate in the development, training, validation, and monitoring of analytical and predictive models; • Apply statistical techniques and machine learning to generate insights and intelligent solutions; • Develop and integrate solutions using Generative Artificial Intelligence and Large Language Models (LLMs); • Integrate AI solutions into products, services, and business processes; • Ensure best practices for code versioning using Git; • Document solutions, pipelines, and data processes; • Work collaboratively with multidisciplinary teams in agile environments; • Contribute to the continuous evolution of data and AI engineering architecture and practices.

• Lead onboarding, implementation, and technical support efforts for institutional clients adopting Tutor.com services. • Manage implementation timelines, launch activities, training programs, and client communications to ensure successful deployments. • Build strong relationships with institutional stakeholders while serving as a trusted advisor throughout the client lifecycle. • Support client integrations with Learning Management Systems (LMS), authentication platforms, and student information systems. • Provide expertise on technologies and standards including LTI, SAML, CAS, and Shibboleth. • Partner with Product, Engineering, Operations, and Customer Success teams to resolve technical issues and improve implementation processes. • Analyze institutional usage, engagement, and outcomes data to identify trends, opportunities, and areas for program optimization. • Develop client-facing reports, dashboards, visualizations, and presentations that communicate program effectiveness, ROI, and student impact. • Translate complex datasets into actionable insights that support strategic decision-making for both clients and internal stakeholders. • Support development of scalable reporting processes, analytics best practices, and data governance standards. • Collaborate across teams to improve reporting workflows, implementation processes, and client-facing tools. • Contribute to strategic client reviews, renewals, and impact discussions through data-driven storytelling and recommendations.

• Act as the bridge between Data Engineering and Marketing Analytics, designing, building, and maintaining robust ETL pipelines and 'Gold Layer' tables in Databricks. • Develop and document semantic layers, data dictionaries, and markdown files designed specifically to train and enable AI agents for scalable, self-serve BI. • Develop dashboards and analyses to surface business-critical KPIs and assess sales and marketing performance. • Perform ad-hoc reporting and deep dives to uncover key insights across programs and initiatives to inform strategy and decision making. • Partner with marketing stakeholders to translate complex business requirements into scalable data models and analytics-ready datasets. • Champion, role model, and embed Samsara’s cultural principles as we scale globally.