• Build and maintain marketing automation and data flows (imports/exports, list syncs, form/UTM capture) to keep lead and contact records accurate across systems • Set up and maintain dashboards and recurring reporting for marketing performance, lead conversions, email, ads, and campaign ROI • Support lead lifecycle processes: lead handoff, scoring inputs, lifecycle stage logic, and SLA reporting in partnership with RevOps • Execute campaign operations tasks: building lists, ensuring correct segmentation, validating suppression logic, and confirming campaign assets are tracked correctly • Monitor data quality (duplicates, missing fields, invalid values) and run routine cleanup processes; escalate systemic issues with recommendations • Audit and validate conversion tracking across key lead touchpoints (forms, key CTAs, landing pages) to ensure reliable attribution and reporting • Support enrichment and segmentation initiatives (firmographic/role-based data, account matching, intent inputs) to improve targeting • Partner with stakeholders to gather reporting requirements and translate them into clear dashboards, views, and analyses • Proactively identify gaps in tracking, process, or reporting and propose lightweight improvements that reduce manual work and increase confidence in metrics • Assist with system and process documentation to improve consistency and onboarding • Contribute to special projects such as new tool evaluations, system migrations, and automation enhancements

• Engage with team members to validate and iterate the models that drive our analytics. • Develop an understanding of algorithms, the technologies and platforms supporting products, and proprietary educational content. • Synthesize knowledge into actionable tests to build modules that assist in identifying academic needs of each individual student. • Collaborate with a team that thinks outside of the box to improve education through the creation of data infrastructure and insightful analytics.

• Collaborate Business Analysts to translate business requirements into scalable and efficient data analytics solutions utilizing Microsoft technologies. • Exhibit in-depth knowledge and hands-on experience architecting solutions with Microsoft Fabric, Azure Synapse Analytics, Azure Data Services, Power BI, SQL Server, Azure Analysis Services, and other relevant Microsoft tools. • Develop end-to-end data analytics architectures, including data integration, data warehousing, data modeling, data visualization, and reporting, leveraging Microsoft platforms. • Review existing and data architectures to identify gaps, recognize risks, recommend improvements, and ensure alignment with enterprise standards and future scalability. • Implement data integration pipelines using Microsoft Azure Data Factory, Azure Data Lake, and other relevant tools to extract, transform, and load data from various sources into a unified data platform. • Create visually appealing and interactive dashboards, reports, and visualizations using Microsoft Power BI, enabling users to gain valuable insights from data. • Identify performance bottlenecks and implement optimizations to improve data processing, query performance, and overall system efficiency. • Partner with our Security practice to ensure data security, privacy, and compliance with relevant regulations and standards are met. • Collaborate with cross-functional teams, providing technical leadership and guidance to clients, data engineers, analysts, and other stakeholders to ensure successful project delivery. • Keep abreast of the latest advancements in data analytics technologies (Microsoft based and others) and industry trends, continuously enhancing your expertise and applying best practices in solution design and implementation.

• Define key KPIs, product metrics, and reports that drive decision making at the highest level. • Design, build, and evangelize source-of-truth reporting tools for finance, sales ops, and technical product executives, to arm them with the needed information to drive their day to day decision making. • Lay the foundation for the growing analytics team to empower cross functional engineering and product teams to make data driven decisions and fast experimental iteration. • Build and publish data visualization and dashboards for exec visibility into product, sales and operations data