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.

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.

Benefits

• experience our caring culture, and enjoy work-life balance.