Senior Marketing and Data Analytics Manager

At Curriculum Associates, we believe in the potential of every child and are changing the face of education technology with award-winning learning programs like i-Ready that serve a third of the nation’s K–8 students. For more than 50 years, our commitment to making classrooms better places, serving educators, and supporting accessible learning experiences for all students has driven the continuous improvement of our innovative programs.

Our team of more than 2,500 employees is composed of lifelong learners who stand behind this mission, working tirelessly to serve the educational community with world-class programs and support every day.

The Senior Marketing and Data Analytics Manager owns the execution of Growth Marketing’s analytics and data operations — building and maintaining the reporting infrastructure that connects marketing activity to pipeline and revenue. Reporting to the VP, Growth Marketing, this role translates the full-funnel reporting framework into day-to-day marketing intelligence, with a focus on data governance, segmentation execution, funnel analysis, and dashboard maintenance.

This role partners with offshore resources and AI tooling to extend capacity, and works closely with IT and Sales Ops to keep Marketing data accurate, complete, and integrated into the broader revenue analytics picture.

Marketing Analytics and Reporting Own Marketing’s contribution to the Growth Marketing Reporting Framework — tracking funnel metrics from awareness through opportunity creation, ensuring data accuracy across Salesforce, Pardot, BI platforms, and Google Analytics.

Partner with IT Data and Analytics and Sales Ops Analytics to deliver integrated, full-funnel reporting that connects marketing activity to revenue outcomes.

Identify performance trends, anomalies, and optimization opportunities across paid media, email, web, and regional marketing programs; translate findings into clear recommendations for marketing leadership.

Develop and maintain executive-ready dashboards and scorecards in Salesforce or other BI platforms; ensure Growth Marketing leadership has real-time visibility into KPIs without manual intervention.

Build and maintain a consistent measurement framework for campaign performance including attribution modeling appropriate for long, complex K-12 buying cycles.

Data Governance and Segmentation Own UTM and tracking standards across all paid and owned channels — define, document, and enforce the framework to ensure consistent campaign attribution and source reporting.

Execute contact database segmentation in Pardot/Account Engagement, supporting demand generation, ABM, and nurture programs with clean, targeted audiences.

Own data hygiene protocols — establish and enforce standards for lead data normalization, deduplication, field governance, and source tracking across Salesforce and Pardot.

Audit existing marketing data infrastructure; identify gaps and redundancies; lead remediation in partnership with IT and Sales Ops to eliminate duplicative work.

Cross-Functional Partnership Serve as Growth Marketing's primary liaison to IT Data and Analytics and Sales Ops Analytics; align on shared data models, pipeline definitions, and reporting cadences.

Coordinate with Sales Ops on lead-to-opportunity conversion metrics, BDR performance data, and pipeline velocity reporting to support the lead to opportunity optimization.

Advise on martech data integrations (e.g., intent data from Zoom Info/Bombora/6

Sense) to ensure new tools are properly instrumented and reportable.

AI and Offshore Resource Leverage Direct dotted-line India-based analytics and GTM resources on high-volume, repeatable data tasks including list processing, data normalization, campaign record creation in Salesforce, and ad-hoc reporting support.

Define KPIs and performance goals for offshore resources aligned to team priorities; QA deliverables to ensure accuracy standards are met.

Identify and implement AI-assisted workflows to automate manual analytics tasks — including report generation, anomaly detection, segmentation builds, and data QA — reducing time spent on low-value work.

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