Marketing Analyst

Overview

As Marketing Analyst at Gearset, you will build and steer our marketing analytics from the ground up, turning raw data into strategic direction. You’ll bridge Marketing, GTM, and Data teams to create a reliable, accessible data foundation that informs growth decisions. You will act as the link between marketing performance and company growth drivers, delivering insights that drive value and data-driven improvement. This role offers the chance to shape our analytics capabilities, dashboards, and data models in a fast‑growing SaaS environment.

Pay / Benefits

• hybrid working
• salary 65k-75k
• personal development budget up to 1500 per year
• Long Term Incentive Plan
• 25 days holiday + bank holidays
• Bupa health care and dental insurance

Responsibilities

• Consolidate marketing data with Data Engineering to enable analytics and reporting
• Produce meaningful business metrics with the Marketing team to monitor performance
• Diagnose fluctuations and assess impact of campaigns using data models and KPIs
• Deliver deep-dive analyses to identify opportunities and measure campaign impact
• Contextualise performance shifts against market conditions, seasonality, product changes, and competitors
• Extend the semantic layer, build accessible dashboards, and enable self-serve data exploration for teams
• Promote data-driven habits and tool adoption across Marketing

Key requirements

• Proven track record building marketing analytics capabilities in ambiguous, fast-growing environments
• Strong commercial acumen with ability to translate complex data into actionable narratives for senior GTM leadership
• Experience presenting to and influencing senior stakeholders
• Strong SQL skills with hands-on dbt, and experience with cloud data warehouses (Snowflake, BigQuery, or Redshift) and BI tools (Omni, Looker)
• Experience with attribution modelling and/or testing methodology (incrementality testing, holdout groups, MTA)
• History of analyses that directly changed marketing decisions
• Deep experience analyzing complex, long B2B buyer journeys across CRM, web/intent, and ad tech data (MQL to won)

• Stakeholder influence and communication
• Curiosity and proactive problem-solving
• Cross-functional collaboration
• SQL
• dbt
• Snowflake/BigQuery/Redshift

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