Growth Marketing Strategy & Planning Manager

Oakland, California, United States, AMER · USA - Denver · USD 150,573-188,216 · Hybrid · Posted Oct 6, 2026

At a glance

Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions.
As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.

The Growth Marketing Strategy and Planning Manager sits at the intersection of B2B marketing strategy and performance analytics.
This role acts as the right hand to the VP of Growth, helping to determine budget allocation, set marketing-level targets, and maximize revenue yield from demand.
The position involves high visibility and direct exposure to marketing leadership, requiring the ability to translate performance data into actionable investment decisions.

Own annual and quarterly target setting for the Growth marketing organization, including channel-level targets and budget allocation.
Support annual budgeting and in-quarter re-planning with recommendations on investment levels and channel mix.
Own marketing ROI analysis, including reporting on cost-per-lead, cost-per-opportunity, CAC by channel, and marketing efficiency ratios.
Design and maintain models to quantify the impact of marketing programs across the buyer journey.
Conduct ad hoc deep dives to diagnose pipeline trends, marketing channel performance, or funnel conversion issues.
Support the weekly and monthly business review process by preparing data and building narratives for leadership.
Drive alignment on ICP across product marketing, product, sales, and marketing.
Own the Growth pipeline model, aligning sourced and influenced contribution across partner, sales, BDR, and marketing.
Analyze marketing experiments to drive continuous improvement and partner with the Head of PLG Revenue to identify friction in the self-serve funnel.
Own capacity and headcount planning for the Growth marketing organization, tying resourcing to targets and coverage requirements.

4 to 7 years of experience in marketing analytics, GTM/marketing strategy, revenue operations analytics, FP&A, or business intelligence within a B2B SaaS environment.
Strong planning and financial-modeling skills, including building target, budget, and pipeline-coverage models.
Ability to independently structure ambiguous problems and drive them to clear, actionable recommendations.
Clear point of view and confidence to challenge assumptions and bring data-backed perspectives to senior stakeholders.
Understanding of B2B SaaS performance metrics such as pipeline, ACV, conversion rates, velocity, and attribution concepts.
Comfortable with SQL, Excel/Google Sheets, and BI/visualization tools like Looker.
Working knowledge of Salesforce, marketing automation platforms (Marketo preferred), and ad platforms.

Python or R proficiency for statistical analysis, automation, or building lightweight models.
Experience with multi-touch attribution platforms (Bizible/Marketo).
Exposure to experiment design, significance testing, or applied statistics in a marketing context.
Experience with predictive modeling: LTV estimation, propensity scoring, or cohort analysis.
Familiarity with the modern data stack (Fivetran, dbt, Snowflake, Looker).

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