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Marketing Data Engineer
Job in
Jacksonville, Duval County, Florida, 32290, USA
Listed on 2026-02-07
Listing for:
Lee Hecht Harrison
Full Time
position Listed on 2026-02-07
Job specializations:
-
IT/Tech
Data Analyst, Data Engineer
Job Description & How to Apply Below
Overview
Description
Position at LHH (Global)
Marketing Data Engineer
This role builds the data foundation and reporting infrastructure for Marketing. By combining data engineering and visualization, this position ensures that Marketing leaders have scalable, automated, and real-time insights. You will build and maintain the data infrastructure that powers all marketing analytics, ingesting platform data and designing warehouse models to transform complex marketing performance data into clear, compelling dashboards and stories.
This role ensures stakeholders across the Marketing and leadership teams have intuitive, self-serve access to the metrics that drive decision-making and growth.
- Reports to Director of Marketing Analytics
- No direct reports
- Remote: US, Europe, India
- Must be proficient in English (speaking, writing, presentation)
- Design, develop, and implement a robust, scalable data architecture that integrates data from ad platforms (Google Ads, Linked In, Meta), multiple CRM instances (Salesforce), marketing automation (Pardot/Marketing Cloud), Website (GA4), and finance systems into a central data warehouse (Fabric/Azure Synapse Workspace), enabling a single source of truth for marketing performance analytics.
- Build and optimize data models that connect different data sources and show an integrated view of the buying journey, supporting reliable channel/campaign multi-touch attribution, ROI analysis, and predictive analytics.
- Implement data governance practices, ensuring accuracy, completeness, and compliance with the company’s privacy rules.
- Partner with Finance analysts to automate marketing spend categorization and revenue reconciliation to power ROI and CAC reporting.
- Collaborate with analysts in Marketing and Sales Ops to provide clean, well-structured datasets for dashboards and advanced modeling (e.g., attribution models, churn prediction, funnel optimization).
- Monitor data pipelines for performance and proactively address quality issues before they impact stakeholders, interacting with IT partners when necessary.
- Leverage the built data models to design, develop, and maintain marketing dashboards in BI tools (Salesforce, Looker Studio, Power BI) to track pipeline health, channel performance, and ROI.
- Collaborate with CRM, Finance, Web Analytics, and Sales Ops teams to combine data from Salesforce, marketing automation, Finance, and digital platforms into unified dashboards.
- Support the creation of standardized visual templates for executive reporting and board presentations.
- Apply UX principles to ensure dashboards are intuitive, interactive, and actionable for stakeholders across Marketing, countries, and the Leadership team.
- Build documentation that helps to train business users on self-serve dashboard access and interpretation of key B2B metrics (pipeline, funnel conversion, campaign ROI and more).
- Continuously improve visualizations by gathering stakeholder feedback and implementing enhancements.
- Bachelor’s degree in Business, Information Technology, Data Science, Computer Science, or a related field.
- 4+ years in data engineering with a focus on marketing or revenue operations and dashboard development for B2B organizations.
- Proficiency in SQL and at least one ETL/ELT framework (Azure, dbt, Airflow, Fivetran, Stitch, etc.).
- Strong understanding of B2B marketing data structures—CRM objects, campaign hierarchies, opportunity stages, GA4, and ad platform APIs.
- Experience with cloud data warehouses and version control.
- Collaborative mindset to work with marketers, analysts, and finance partners in a matrix environment.
- Advanced skills in one or more BI tools (Power BI recommended).
- Eye for design and storytelling to help communicate complex funnel metrics clearly.
- Passion for enabling teams to make data-driven decisions quickly and confidently.
- Excellent analytical skills with the ability to interpret complex data sets.
- Strong problem-solving skills and attention to detail.
- Effective communication skills with the ability to present technical information to non-technical stakeholders.
- Ability to work independently and collaboratively in a fast-paced environment.
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