Senior Data Analyst (Marketing Experience)

Role Overview

Senior Data Analyst focused on Marketing Experience, working in a remote-first environment with enterprise clients. You will turn complex, multi-source marketing data into clear, actionable insights that improve business performance.

Responsibilities

• Own end-to-end delivery for assigned client accounts, translating business needs into structured analytics solutions
• Build, maintain, and optimize dashboards and reports in BI tools (Looker, Power BI, or Tableau)
• Design and optimize scalable data models integrating multiple marketing sources (e.g., CRM, ad platforms, web analytics)
• Develop, troubleshoot, and optimize SQL queries for reporting, analysis, and investigation
• Manage transformations using dbt and ensure reliable ELT/ETL pipelines
• Map and document complex data flows across multi-source marketing ecosystems
• Conduct QA/UAT and apply data validation practices to ensure accuracy and trust
• Identify trends, risks, and opportunities and communicate insights to clients and stakeholders
• Work cross-functionally with engineering, analytics, and client success

Requirements

• 3+ years hands-on SQL experience in analytics or engineering contexts
• Strong experience with at least one BI tool: Looker, Power BI, or Tableau
• Experience working with multiple marketing data sources simultaneously
• Strong data modeling knowledge (e.g., star schema, dimensional modeling)
• Understanding of ELT/ETL processes and ability to debug transformation logic
• Strong QA/UAT and data validation practices
• Excellent communication skills; able to present to non-technical audiences
• English C1 (written and spoken)
• Ownership mindset, attention to detail, and ability to work independently in ambiguous environments
• Proficiency with AI tools and ability to integrate them into analytics workflows

Nice to Have

• Google Analytics and marketing platforms (e.g., Google Ads, Facebook Ads)
• Marketing attribution or Marketing Mix Modeling (MMM)
• dbt experience in analytics workflows
• Python (or other scripting language) for analysis/automation
• Data observability or data quality frameworks