Senior Marketing Data Analyst

Role Overview

The Senior Marketing Analyst is responsible for developing the marketing performance framework and measuring, optimizing, and analyzing marketing initiatives across channels to drive measurable business outcomes.

What You Will Do

The analyst will build robust data pipelines, merge datasets, and derive actionable insights from user sessions, conversion metrics, and cross-channel performance.

Why It Might Be a Fit

The role requires a strong emphasis on analyzing individual user behaviors, and the ability to translate insights into personalized campaigns and continuous improvements.

Requirements

• Developing the marketing performance framework across channels, campaigns, lifecycle journeys, events, GTM programs, and customer segments.
• Defining KPIs, reporting logic, lead source taxonomy, conversion definitions, funnel stages, and success measures in partnership with Marketing, Customer Intelligence, Sales, Commercial Activation, and Finance.
• Assisting in ingest and structure raw web traffic data into scalable datasets in BigQuery, designing schemas for efficient querying and in-depth analysis of individual user sessions, logged-in behaviors, conversion funnels, and personalization opportunities.
• Partnering with IT to develop ETL processes for cleaning, transforming, and merging web data with other datasets using SQL for complex joins, aggregations, data enrichment, and user-level segmentation.
• Tracking and reporting on digital campaign performance, ROI, and funnel effectiveness across web, email, paid media, and social channels, with a focus on how individual user interactions inform personalized marketing tactics.
• Developing interactive dashboards and reporting frameworks using tools like Power BI to measure marketing effectiveness, monitor user engagement, and support real-time decision-making.
• Analyzing customer behavior and digital engagement at the individual level to identify optimization opportunities, such as tailored content recommendations or targeted retargeting.
• Providing data-driven insights and recommendations to improve conversion rates, retention, and personalization, ensuring compliance with data privacy regulations (e.g., GDPR, CCPA).
• Developing, implementing, and optimizing multi-channel digital strategies (paid search, social, content) to improve ROI and meet business objectives.
• Leading the effort to tag lead sources and conversion events across campaigns, forms, events, paid media, email, social, website content, and CRM-enabled journeys.
• Developing and governing a consistent source, medium, campaign, program, segment, and offer taxonomy so Marketing can connect engagement to leads, opportunities, retention, and revenue influence.
• Building funnel reporting from awareness to engagement, inquiry, qualified lead, opportunity, conversion, retention, and revenue influenced.
• Identifying tracking gaps, data quality issues, duplicate source logic, and attribution limitations, then recommending practical fixes.
• Partnering with Marketing, Sales, and Digital Experience leaders to align campaigns with broader business strategies and personalize user experiences based on website usage patterns.
• Collaborating with the Data & Insights team to maintain consistent measurement, data quality, customer segmentation, and ethical data practices.
• Engaging with the Digital Enablement team in linking web performance metrics to enterprise KPIs.
• Sharing insights, best practices, and training across teams to foster a culture of data-driven, personalized marketing and continuous improvement.
• Supporting ELT, Marketing, and Commercial reporting by connecting marketing performance metrics to enterprise KPIs, including revenue influence, conversion, retention, loyalty, and customer engagement.
• Translating performance insights into recommendations for campaign optimization, audience targeting, budget allocation, lifecycle strategy, and customer-facing enablement.
• Staying abreast of emerging trends in digital marketing, CRM personalization, web analytics tools, and privacy-compliant technologies.
• Testing and piloting innovative approaches, such as A/B testing, multivariate experiments, predictive modeling for user behavior, and advanced personalization strategies (e.g., using machine learning basics for segmentation).
• Championing the adoption of digital-first, user-centric practices within the organization.

Benefits

• Medical/prescription drug insurance
• Dental insurance
• Vision insurance
• Health Savings Account
• Flexible Spending Accounts
• Life Insurance
• Disability Insurance
• 401(k)
• Critical Illness, Hospital Indemnity and Accident Insurance
• Identity Theft and Legal Services
• Paid time off
• Paid Maternity Leave
• Tuition reimbursement
• Training and Development
• Employee Assistance Program (EAP) & Perks

Tagged as: Data Analysis