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Marketing Data Engineer

Lee Hecht Harrison
United States, New Jersey, Woodcliff Lake
Jan 26, 2026
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 andmaintainthe data infrastructure that powers all marketing analytics,ingesting platformdataanddesigning warehouse modelsto transformcomplex marketing performance data into clear, compelling dashboards and stories. This role ensures stakeholders acrosstheMarketingand leadership teamshave intuitive, self-serve access to the metrics that drive decision-making and growth.
Reporting Relationships:
  • Reports to Director of Marketing Analytics
Direct Reports:
  • No direct reports
Location:
  • Remote: US, Europe, India
Languages:
  • Must be proficient in English(speaking, writing, presentation)
In this role you can expect to
Data EngineeringInfrastructure
  • Design, develop, and implement a robust, scalable data architecture that integrates data from ad platforms (Google Ads, LinkedIn, 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 andoptimizedata models that connect different data sources and show a more 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 withcompany'sprivacy rules.
  • Partner with Finance analyst 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 theyimpactstakeholders, interacting with IT partners when necessary.
Data Visualization &Analysis
  • Leverage the built data models to design, develop, andmaintainmarketing 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.
All About You
  • Bachelor's degree in Business, Information Technology, Data Science, Computer Science, orrelatedfield.
  • 4+ years in data engineering with a focus on marketing or revenue operationsand dashboard development for B2B organizations.
  • Proficiencyin 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 (PowerBIrequired)
  • 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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