Marketing Analytics Lead

Sedgwick

About The Position

By joining Sedgwick, you'll be part of something truly meaningful. It’s what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there’s no limit to what you can achieve. Newsweek Recognizes Sedgwick as America’s Greatest Workplaces National Top Companies Certified as a Great Place to Work® Fortune Best Workplaces in Financial Services & Insurance Marketing Analytics Lead PRIMARY PURPOSE OF THE ROLE: The Marketing Analytics Lead builds, maintains, and operationalizes a trusted marketing data foundation that powers reporting, insights, and AI-ready analytics. This role is primarily a marketing data engineering position with secondary responsibility for insights and performance reporting. The Marketing Analytics Lead designs and manages scalable ETL/ELT pipelines and analytics-ready data models across the marketing ecosystem—CRM, marketing automation, paid media, web analytics, and messaging platforms—ensuring data is accurate, governed, and accessible for full-funnel measurement.

Requirements

Bachelor’s degree in marketing or a related field from an accredited college or university preferred.
Six (6) years of experience in marketing analytics, marketing data engineering, data engineering, BI engineering, or closely related roles—preferably in B2B, services, or complex sales cycles, or equivalent combination of education and experience required.
Demonstrated ability to build and maintain ETL/ELT pipelines that integrate data from CRM, marketing automation, advertising, and web/product analytics platforms.
Strong background working with CRM and marketing platforms (e.g., Salesforce/HubSpot; Marketo, Pardot, Braze), including funnel, lifecycle, campaign, and opportunity data.
Proficiency incorporating digital advertising and web analytics data (e.g., Google Ads, Meta, LinkedIn, GA4, Adobe Analytics, Segment) to support attribution and performance measurement.
Deep understanding of data warehousing and analytics engineering best practices, including dimensional modeling and supporting downstream reporting and dashboards.
Experience operating in environments requiring high standards for data quality, governance, privacy, and compliance.

Responsibilities

Marketing Data Engineering (ETL/ELT, Warehousing & Modeling)
Designs, develops, and maintains reliable ETL/ELT pipelines that ingest and unify marketing data from multiple systems (e.g., CRM, marketing automation, paid media, web analytics), ensuring timely and accurate data availability.
Builds and optimizes analytics data stores and curated, analytics‑ready datasets that support scalable reporting, self‑service analysis, and standardized full‑funnel measurement.
Develops and maintains marketing data models and reusable structures that enable core use cases such as campaign performance, funnel and conversion analysis, attribution/influence reporting, and account lifecycle measurement.
Implements and maintains standardized definitions, keys, and documentation (e.g., taxonomies, lifecycle stages, lineage, metadata) to ensure consistent interpretation, data quality, and downstream usability.
Reporting, Insight & Stakeholder Enablement
Builds and maintains dashboards and recurring performance reporting that supports marketing leadership, demand generation, and sales alignment—focused on business outcomes (pipeline contribution, revenue influence, account engagement).
Partners with the Marketing Analytics Director to deliver insights and recommendations by summarizing trends, identifying drivers, and highlighting opportunities for optimization across channels and funnel stages.
Translates stakeholder questions into analytical approaches, ensuring metrics and outputs are clear, actionable, and aligned to documented definitions.
Supports measurement approaches for B2B marketing motions (ABM/account engagement, lead nurturing, sales enablement influence, events/webinars, and partner marketing) by enabling consistent tracking, reporting, and interpretation.
Monitoring, Reliability & Cost/Performance Optimization
Monitors and troubleshoots pipelines and integrations; proactively identifies failure points, resolves incidents, and improves resiliency through alerting, validation checks, and documented recovery steps.
Optimizes queries, storage, and processing costs in cloud and/or on-prem environments by tuning pipelines, applying partitioning/cluster strategies where applicable, and improving transformation efficiency.
Maintains detailed runbooks and operational documentation to support continuity, scalability, and onboarding.
Data Quality, Governance, Security & Compliance
Ensures data quality, accuracy, reliability, and performance across the marketing data ecosystem through validation rules, anomaly detection, automated testing, and monitoring.
Implements data governance best practices, including documentation, data dictionaries, naming conventions, retention guidelines, and access controls aligned with enterprise standards.
Partners with IT, security, privacy, and compliance stakeholders to ensure data handling aligns with regulatory expectations and internal policies (e.g., least-privilege access, PII controls).
Establishes and maintains clear source logic for key marketing entities (accounts, contacts/leads, campaigns, opportunities) within the marketing data domain, including identity resolution and deduplication techniques.
Cross-Functional Collaboration
Collaborates closely with Performance Marketing, Demand Generation, Sales Ops/RevOps, Finance, and IT to align on KPIs, attribution approaches, and data definitions within the marketing measurement ecosystem.
Supports enablement of broader marketing teams through documentation, training, and consultation on how to use datasets and dashboards effectively.
Leads discrete workstreams or small projects by coordinating timelines, requirements, and dependencies across stakeholders without direct people management responsibility.