Senior Marketing Data Analyst

About the Role

Fivetran is building data pipelines to power the modern data stack for thousands of companies.

We’re hiring a Senior Marketing Data Analyst to support our Marketing organization and unlock insights from the rich internal data at Fivetran. This role focuses on analyzing marketing performance, campaign effectiveness, and funnel data to drive growth, optimize spend, and enable smarter decision-making.

You’ll lead high-impact, cross-functional projects and develop trusted relationships with marketing, sales, and product partners. You’ll define and maintain core marketing metrics, own key data pipelines and dashboards, and help shape the team’s analytics culture and best practices. If you love digging into campaign attribution, untangling complex datasets, and turning insight into action — this is your opportunity to make a real impact.

This is a full-time, hybrid position based out of our Oakland, CA office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team.

Technologies You’ll Use

• SQL (BigQuery)


• dbt/SQLMesh


• Looker/LookML


• Sigma/Hex/Google Colab/Google Sheets


• Jira

What You’ll Do

• Define and own Marketing metrics across funnel performance, campaign effectiveness, pipeline contribution, and ROI; establish benchmarks and enable monitoring through dashboards and self-serve tools.


• Analyze diverse datasets (e.g., digital campaigns, website analytics, CRM, product usage, pipeline and revenue data) to generate actionable insights and recommendations that improve efficiency and growth.


• Lead cross-functional projects with Marketing, Sales, Finance, and Product partners in areas such as: campaign attribution and performance, pipeline conversion efficiency, spend optimization, and audience segmentation.


• Analyze marketing experiments (e.g., A/B tests, channel pilots, creative variations) to measure impact, validate hypotheses, and provide clear recommendations for scaling or iterating.


• Investigate anomalies and performance shifts , conducting deep dives and creative exploration across disparate datasets to uncover root causes and opportunities.


• Own and enhance data infrastructure for Marketing Analytics — from metric definitions to data pipelines to dashboards and reporting systems.


• Shape data culture by mentoring junior analysts and establishing best practices in metric design, marketing analytics quality, and data storytelling.

Skills We’re Looking For

• 4+ years of experience analyzing data in a marketing, growth, or go-to-market context


• Advanced proficiency in SQL and data modeling; fluency with large, complex, and cross-functional datasets


• Experience with BI tools such as Looker, Tableau, or similar platforms for building dashboards and visualizations


• Strong attention to detail and a proven track record of analytical rigor in delivering reliable insights


• Excellent communication and storytelling skills — able to simplify complex analyses and influence marketing and business decision-makers


• Comfortable taking ownership of ambiguous problems and developing end-to-end analytic solutions


• Demonstrated success using analytics to drive decisions in areas like campaign performance, funnel optimization, spend efficiency, or revenue impact


• Passion for leveraging data and analytics to shape marketing strategy and drive measurable business impact

Bonus Skills

• Experience working with marketing and funnel-level data (e.g., campaign performance, website analytics, CRM/marketing automation data, or product usage signals)


• Proficiency in Python or R for deeper analysis, statistical modeling, and automation of reporting


• Background in B2B SaaS or growth-focused marketing analytics , ideally in environments with complex funnels, multi-channel attribution, or developer-focused products


• Strong expertise in marketing attribution and ROI analysis, connecting spend and campaigns to pipeline and revenue outcomes


• Applied knowledge of statistical methods (e.g., regression modeling, significance testing, experiment analysis) to evaluate marketing impact and guide decision-making

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