Growth Marketing Job Description: 2025 Hiring Guide

Growth Marketing Job Description

If you are building your first growth team, you want a role profile you can copy, yet you also need context so you hire the right person for your stage. Growth Marketing Job Description: The Complete 2025 Hiring Guide. I have spent over a decade running weekly growth sprints, cutting through vanity metrics, and shipping experiments that compound over time. That perspective shapes everything you will read here, from the definition to a copy-ready job ad template. The goal is simple and very practical: help you hire someone who will move your North Star in the first 90 days and keep moving it quarter after quarter.

Who this Growth Marketing Job Description is for

Hiring managers and founders building their first growth team.
HR or TA partners customizing a role profile and job ad.
Marketers clarifying responsibilities across product, brand, and demand generation.

You will see a bias toward measurable impact, lean processes, and a shipping culture. That bias is intentional. Endless meetings and decks do not create growth. Shipping does.

TL;DR

Role purpose: Drive acquisition, activation, retention, referral, and revenue across the full funnel with experiment-led, data-informed marketing. Scope: Own paid, owned, and earned channels. Orchestrate a durable experimentation engine. Optimize journeys. Collaborate tightly with product, sales, data, and customer success. Outcomes: Efficient growth that lowers CAC and raises LTV, produces measurable ROI, and builds a compounding library of learnings.

I prefer to simplify reporting to one or two real metrics that feed the North Star and stop surfacing fluff like impressions or generic awareness (use those only to diagnose, not to declare victory).

What is a Growth Marketing Manager? (Definition and business impact)

A Growth Marketing Manager is a data-informed operator and team player who is accountable for sustainable user and revenue growth. The best ones balance analysis with creative testing and strong customer insight. They live in the experiment backlog and in the conversations with product, sales, data, and CS, so growth work aligns with company OKRs and actually ships every single week.

The difference between a good hire and a great one shows up in experiment cadence and learning quality. In my own practice, executing hundreds of experiments with a documented success rate taught me that velocity is nothing without a learning agenda and that learnings are nothing without decisions and follow-ups that scale winners and cut losers.

Role placement and reporting lines

Typical reporting: Head or Director of Growth, VP Marketing, or directly to the GM or CEO in earlier stages.
Team topology: A cross-functional squad model with Product, Data, Design, Engineering, Sales, and Customer Success works best when KPIs are shared and the experimentation cadence is explicit.
Why this matters: Growth only compounds if the loops are designed around your product’s value, not around channel silos.

Key Responsibilities (mapped to AARRR plus experimentation and collaboration)

Strategy and planning

Define ICPs and segments, edge cases, and the growth thesis for each.
Map the customer journey and identify friction to first value.
Establish KPIs and OKRs, including revenue and payback modeling.
Publish a rolling experiment roadmap with clear hypotheses, power calculations where relevant, and success criteria.
Keep the metric stack simple (one aspirational North Star and one tactical driver) so the team focuses on what actually moves the business.

Acquisition (A of AARRR)

Orchestrate multi-channel programs across SEO, SEM, paid social, display, partners, and communities.
Plan content that fuels discovery and demand (blogs, programs, webinars, short video) with intent in mind.
Manage budgets to ROAS and CAC targets.
Treat landing pages as products and iterate quickly.

A note on organic: ROI-driven SEO is not a slogan. It starts with a quantified opportunity model, a syntax or topical gap analysis, and a backlog that prioritizes shippable improvements over theory.

Activation and Onboarding (retention starts here)

Drive conversion rate optimization across signup, onboarding, and first-value moments.
Instrument lifecycle programs across email, in-app, and push to accelerate time-to-first-value.
Apply behavioral science deliberately. Anchoring, framing, and decoys can guide the first meaningful choice, like the plan a new user selects or the first task they complete.

Retention and Monetization

Build lifecycle streams for nurture, upsell, cross-sell, and win-back.
Run pricing and packaging experiments, including paywall positioning and trial design.
Track cohorts, not just aggregates, so you see the impact of changes on survival and expansion revenue.

Precision and simplicity in UX matters here. Reducing choice overload, clarifying the next best action, and improving aesthetic usability reduces friction and increases perceived value.

Referral and Advocacy

Launch and optimize referral programs, UGC collecting, community prompts, and review flows.
Use social proof ethically and make it easy for satisfied users to share. The right placement of proof and the right framing nudge action without adding complexity.

Analytics and Experimentation

Design A/B and multivariate tests and maintain a clear learning agenda.
Own instrumentation requirements, events taxonomy, and source-of-truth dashboards.
Report with clarity. Bring decisions, not just charts.

My strong recommendation is a weekly sprint rhythm where something that drives growth gets shipped every week, even if it is a small bet. That rhythm compounds skill and results over time.

Collaboration and ways of working

Partner with Product on roadmap and experiment design.
Partner with Sales and RevOps on definitions and feedback loops from MQL to Closed Won.
Partner with CS on retention and expansion playbooks and close the loop on NPS or CSAT insights.

I have found that documenting growth loops and meeting only to unblock decisions protects the team’s time and keeps the pipeline of experiments healthy.

Own a pragmatic editorial calendar aligned to growth goals.
Write with a human voice and avoid buzzword salad. For example, skip the em dash and cut filler so readers stay with you (your candidates will thank you for that too).

Market and Trend Scanning

Evaluate new channels, formats, and martech.
Keep a backlog of “small, safe” tests and a shortlist of “bigger bets” that need dedicated discovery.

Required Skills and Experience

Analytical strength: SQL or Sheets proficiency, experimentation literacy, cohort and retention analysis, ability to convert insight into action.
Digital marketing depth: SEO and SEM, paid social, email or SMS, CRO, marketing automation, and attribution.
Martech proficiency: MAP or CRM, product analytics, testing platforms, and working comfort with CDP or ETL basics.
Communication and collaboration: Clear writing, stakeholder management, sprint rituals, concise reporting.
Track record: Portfolio of experiments, not just outputs. Show problem, hypothesis, design, result, and what changed.
Customer lifecycle fluency: AARRR, growth loops, and journey mapping as working tools, not decorative frameworks.

Nice to have: product-led growth experience, mobile or app growth, basic HTML or CSS or JS, design sensibility, and data visualization.

Success metrics and KPIs

Pick a small set of North Stars for your stage across the funnel, then instrument the path to each:

Acquisition: traffic by intent, CVR, CAC, ROAS.
Activation: time to first value, onboarding completion, first action rate.
Retention: D1 or D7 or D30, churn by cohort, expansion rate.
Revenue: ARPA, LTV, payback period.
Referral: share rate, K-factor.

Keep the stack simple so energy goes to experiments that move the one or two numbers that matter.

Measure the experimentation engine itself too: velocity, win rate, incremental lift, and documentation completeness. In practice, I like win rate combined with “lift per shipped experiment” and the percentage of experiments that drive a production change within 14 days. That mindset is how hundreds of experiments translate into reliable growth lift over time.

Tooling and tech stack (by workstream)

Data and analytics: GA4, product analytics, and BI to stitch the story end to end.
Acquisition: ads platforms, SEO tooling, and channel measurement.
Lifecycle: marketing automation for email, in-app, SMS.
Experimentation and CRO: client or server-side testing, user journey insight.
Collab and PM: project management, documentation, and design collaboration.

Your exact stack will vary. The important part is how you use it. In my teams, simple combinations like a landing page builder paired with disciplined testing and a lean freelance bench can deliver fast cycles and real savings when you are ROI minded.

Day in the life (a practical 90-day plan you can hand to your new hire)

Days 0–30

Audit data, funnels, and tracking.
Align on one or two KPIs that feed the North Star.
Fix top instrumentation gaps.
Ship three to five quick wins that improve first value or first conversion.

Days 31–60

Stand up the experiment engine and weekly growth sprint.
Launch two or three multi-channel plays tied to a single thesis.
Publish dashboards that are decision friendly.

Days 61–90

Scale winners and cut losers with explicit criteria.
Propose next quarter’s growth thesis, budget, and resourcing plan.
Document what you learned and what it changes.

A weekly shipping rhythm is the backbone here. It builds momentum and keeps the team honest about what truly moves the metric.

Sample Growth Marketing Job Description (copy-ready)

Title: Growth Marketing Manager

About the role (mission and business context): You will own full-funnel growth across acquisition, activation, retention, referral, and revenue. Your goal is to drive efficient growth with a repeatable experimentation engine and cross-functional collaboration that aligns to company OKRs.

Responsibilities:

Strategy and planning for ICPs, journey mapping, and KPIs.
Acquisition across SEO or SEM or paid social or partnerships.
Activation and onboarding flows that accelerate time to first value.
Retention and monetization through lifecycle programs and pricing experiments.
Referral and advocacy programs that compound.
Analytics and experimentation design, taxonomy, and dashboards.
Collaboration with Product, Sales or RevOps, and CS.
Content and social programming that supports growth goals.
Market scanning and test backlog maintenance.

Requirements:

Analytical strength, experimentation literacy, and cohort analysis.
Channel depth in SEO or SEM, paid social, email or SMS, CRO, and automation.
Proficiency with MAP or CRM, analytics, testing, and CDP or ETL basics.
Clear writing, stakeholder management, sprint rituals, and concise reporting.
Portfolio of experiments with outcomes and what changed.
AARRR and growth loop fluency.

KPIs: List the five to seven metrics that actually matter for your model, such as CAC, payback, TTFV, D30 retention, ARPA, and LTV.

Compensation and location: Include range, equity eligibility, and work style expectations.

How to apply: Ask for a portfolio of experiments, dashboards, and outcomes.

Write the ad in human language and keep it free of clichés or em dashes. Your candidates will notice the clarity.

Collaboration model and RACI

Define the DRI for core workflows: campaign launch, experiment review, lifecycle changes, and attribution updates. Keep cadence predictable: a weekly growth standup, a biweekly experiment review, and a monthly QBR that is decision heavy. I recommend documenting your growth canvases and loops so everyone understands how the work maps to KPIs.

Career path and progression

Offer two tracks and make both prestigious:

Individual contributor: Growth Marketer to Senior to Principal (scope expands to own systems and company-level levers).
Management: Manager to Lead to Director to VP (scope expands to portfolio leadership and coaching).

Assess on craft, impact, scope, leadership, and autonomy. A solid growth org values the operator who ships, as much as the leader who designs the system where shipping is the culture.

Legal and compliance notes

Growth teams handle data. Note how you handle consent, retention, and deletion. Make accessibility part of your definition of done. Brand safety matters too, especially when you test new channels or formats.

FAQs

What does a Growth Marketing Manager actually do day to day? They plan and execute experiments that drive AARRR outcomes. They translate customer insight into hypotheses, ship tests, measure impact, and partner across the org to scale what works.

How is growth marketing different from digital or product marketing? Growth owns the whole journey, not just awareness or conversion. It is experiment-led and revenue accountable. It forces clarity on metrics and uses behavioral science carefully to guide users to value.

Where should this role sit organizationally? Place it where it can ship with speed and collaborate with product and revenue teams. Early on, reporting to a GM or CEO can work. Later, a Head of Growth or VP Marketing is common.

What should success look like in 90 days? Clear instrumentation, a weekly shipping cadence, a backlog with decisions, at least a few scaled winners, and a documented thesis for the next quarter.

Appendix (plug-and-play)

Example experiment backlog template

Hypothesis
Segment and step in journey
Expected impact on KPI
Test design and minimum detectable effect
Implementation owner and required support
Start date and stop date
Result and decision
Follow-ups and documentation link

Sample KPI dashboard widget list

North Star and one driver metric (levels and trends).
Acquisition by intent and cost, with CVR.
Activation funnel with drop-offs and time to first value.
Retention by cohort and plan.
Revenue by ARPA and LTV, payback distribution.
Referral events and share rate.
Experiment velocity and lift.

Interview question bank

Tell me about a hypothesis you killed early and why.
Show me a lifecycle change that improved retention. What signal told you to try it?
How do you choose between a pricing test and a paywall test?
Walk me through a time you changed your ICP or messaging based on user interviews.
Share a time when an experiment failed but changed your roadmap.

Take-home brief

Provide a 30-60-90 plan for a product with activation friction in onboarding.
Design two experiments to improve time to first value.
Create a simple metric stack and a single dashboard mockup.
State what you would ship in week one.