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Marketing Analytics Lead

Job in Nashville, Davidson County, Tennessee, 37247, USA
Listing for: Sedgwick
Full Time position
Listed on 2026-03-10
Job specializations:
  • IT/Tech
    Data Analyst, Data Security
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

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.

ESSENTIAL

RESPONSIBILITIES MAY INCLUDE 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…
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