• Own, maintain, and improve core data systems including dbt, Stitch, and the BigQuery data warehouse sourced from NoSQL datasets (e.g., Firestore). • Develop reliable, well-documented data models, transformations, and ELT pipelines supporting revenue, operational, and financial reporting. • Implement and maintain data quality and observability frameworks, including dbt tests, schema-change monitoring, and pipeline alerts. • Be the BigQuery expert to apply version control, documentation, naming conventions, and workflow best practices for long-term maintainability. • Build, maintain, and optimize Google Looker Studio dashboards, ensuring accuracy and usability. • Perform ongoing dashboard maintenance, enhancements, and metric updates as business needs evolve. • Build and maintain recurring operational reports, including those used for enterprise customer audits and sales pipelines. • Partner closely with Finance, Operations, and Customer-facing teams to translate business needs into actionable analytics and data workflows.

• Design, build, and maintain interactive dashboards and reports in Amazon QuickSight • Translate business requirements into clear and useful visualizations • Create, manage, and optimize datasets and data sources • Write and maintain SQL queries to support reporting and analytics needs • Ensure data accuracy, consistency, and performance across dashboards • Partner with data engineers, analysts, and business users to refine metrics and KPIs • Document dashboards, datasets, and data definitions for long-term maintainability • Support users with basic troubleshooting and dashboard enhancements

• Gather and analyze data from several databases and other sources to perform analyses and build reporting solutions to support our internal stakeholders • Code, build and maintain complex reporting solutions using MS SQL, Power BI, and other reporting tools • Collaborate directly with university stakeholders to gather business requirements, interpret metrics, and deliver iterative analyses in response to ad-hoc needs • Advise and assist partners in determining the appropriate analytical methodologies to address business questions/problems/objectives • Create and present executive-level visualizations and analyses to business partners, collaborating to interpret results and deliver clear, actionable recommendations that incorporate stakeholder feedback • Translate complex technical concepts for non-technical audiences • Design and assist with implementation of process improvement initiatives • Collaborate with other Analysts, Analytics Engineers and our Data Warehouse team, to ensure consistency of reporting, minimize duplication of effort, and identify/rectify limitations in data sources • Contribute to the evolving use and exploration of AI-enabled tools within our Analytics team • Actively participate in data governance initiatives

• Development and maintenance of dashboards in Power BI and performing deep analytics in Excel (OLAP cubes). • Writing advanced DAX measures. • Enhancing the analytical data warehouse (DWH). • Designing data models for BI needs, creating new business entities not present in source systems, and performing gradual refactoring of legacy structures. • Developing complex ETL processes in Python (API integrations, parsing, custom scripts). • Maintaining pipelines in Apache Airflow. • Analyzing, reverse-engineering, and optimizing existing data structures. • Writing complex SQL queries (PostgreSQL, MariaDB) and analyzing T-SQL to understand the structure of MS SQL–based systems. • Configuring and supporting automations in Power Automate (e.g., auto-refreshing Excel reports, Outlook email flows). • Ensuring data consistency, identifying metric discrepancies across CRM databases, and resolving anomalies. • Collaborating with stakeholders to translate business requirements into technical BI solutions.