Marketing Analyst Job Posting Template & Checklist

This tutorial gives you a copy-paste Marketing Analyst job posting built for technology companies, plus schema and SEO steps to publish it today. You’ll also get a distribution plan, assessment rubric, and compliance notes so you attract qualified applicants fast and fairly. If you’re publishing a marketing analyst job posting in technology company blog environments, this guide keeps you on-brand, compliant, and measurable.

Hiring across SaaS and product-led teams shows one truth: clarity beats cleverness. A sharp, inclusive posting with concrete outcomes, required skills, and a clean apply flow increases qualified apply clicks and reduces time-to-hire. Use the template and checklists below to move from draft to live in under an hour.

Who You’re Hiring: The Marketing Analyst Role in a Tech Company

Decide on the role based on business impact, not tool lists, so candidates self-select for outcomes. In a technology company, a Marketing Analyst connects channel and product data to pipeline and revenue. They improve attribution quality and enable faster experimentation decisions.

They partner with Growth, Product Marketing, Sales Ops/RevOps, and Data to drive profitable acquisition and expansion. The best analysts mix SQL rigor with clear data storytelling and stakeholder alignment. Aim your posting at outcomes and responsibilities, then list the tech stack needed to deliver them.

Set expectations with examples of shipped work that changed results. A strong fit has shipped analyses that:

• Changed budget allocation
• Improved conversion through experimentation
• Instrumented tracking that withstood stakeholder scrutiny

For example, migrating to GA4 + BigQuery with modeled conversions and then validating attribution against CRM opportunity stages. Your takeaway: state the outcomes and KPIs you expect, then back them with the required environment (warehouse, BI, product analytics, experimentation).

Core outcomes and KPIs in tech (pipeline, CAC/LTV, attribution quality, experimentation velocity)

Focus the role on measurable business impact. List the KPIs you expect the analyst to influence so candidates self-qualify.

• Pipeline and revenue influenced/attributed (by segment and channel)
• CAC, payback period, LTV/CAC, and cohort retention by acquisition source
• Attribution accuracy/coverage (modeled vs. last-touch, offline/online match rates)
• Experimentation velocity (tests launched per month) and win rate; uplift with confidence intervals
• Funnel conversion rates (lead → MQL → SQL → Opp → Closed Won) and drop-off diagnostics
• Data quality SLAs (event coverage, tracking accuracy, tag health, UTM hygiene)
• Budget reallocation impact (incrementality and MMM/GeoLift insights, where applicable)

Common title variants: Marketing Analyst vs Digital Marketing Analyst vs Growth Analyst

Choose the title that best fits the scope and talent market. Titles signal seniority and toolsets and affect search and applicant pool quality.

• Marketing Analyst: Broad analytics across channels, funnel, and revenue; partners with Product/RevOps; often includes SQL + BI + GA4. Use when scope spans acquisition to pipeline.
• Digital Marketing Analyst: Emphasis on web, paid media, SEO/SEM, and conversion rate analytics; often lighter on product data. Use for channel-focused roles without deep product/warehouse work.
• Growth Analyst: Strong experimentation, lifecycle, and product analytics; heavy SQL, event tracking, and causal inference. Use when embedded in Growth with A/B testing and activation/retention ownership.

Copy-Paste Marketing Analyst Job Posting Template (Tech-Ready)

Use this modular template to publish a high-signal, inclusive marketing analyst job posting. Swap in the bullets that match your stage and stack, and keep pay transparency and application instructions intact for compliance and candidate trust.

Role summary (SaaS/product-led context)

Write a crisp, candidate-facing summary that ties the role to outcomes and the stack they’ll use.

• We’re hiring a Marketing Analyst to turn multi-channel and product data into actionable growth decisions. You’ll own acquisition and funnel analytics across GA4/BigQuery, our paid channels, and the CRM, improving attribution quality and informing budget, experimentation, and forecasting.
• You’ll partner with Growth, Product Marketing, and RevOps to define KPIs, build self-serve dashboards in Looker/Looker Studio, and ship insights that shift spend and accelerate pipeline.
• Ideal candidates are fluent in SQL and have shipped analyses that improved CAC/LTV, validated attribution, and increased test velocity.

Responsibilities (choose by maturity: early-stage, growth-stage, enterprise)

Select the bullets that match your company stage. Keep scope realistic.

• Early-stage
• Stand up marketing analytics foundations: event tracking plan, GA4 + BigQuery export, UTM governance, and baseline dashboards.
• Build core funnel and cohort views from warehouse sources (product events + CRM + billing).
• Run lightweight experiments (landing pages, onboarding flows) and report uplift with clear assumptions.
• Partner with paid media to test creative/audience hypotheses and reallocate budget quickly.
• Growth-stage
• Own attribution strategy (modeled/multi-touch) and reconcile with CRM pipeline and revenue.
• Design and analyze A/B tests across paid, website, and lifecycle channels; define guardrails and power.
• Lead monthly marketing performance reviews; recommend budget and channel mix changes.
• Maintain BI dashboards (Looker/Looker Studio) and data quality SLAs; drive self-serve adoption.
• Enterprise
• Collaborate with Data Engineering on CDP/ETL integration (e.g., Segment/Fivetran) and governance.
• Partner with FP&A on forecasting, MMM/GeoLift, and incrementality testing where budgets support it.
• Standardize experimentation frameworks, peer review, and documentation across teams.
• Mentor analysts; establish analytics best practices and stakeholder education.

Required skills and tech stack (SQL/BigQuery, Python/R, GA4, Looker/Looker Studio, Amplitude/Mixpanel, A/B testing)

List true must-haves to widen the qualified pool while maintaining rigor.

• Proficiency in SQL (e.g., BigQuery, Snowflake, Redshift); ability to write joins, CTEs, and window functions
• GA4 with BigQuery export; event-tagging literacy and consent-aware tracking
• BI/dashboarding (Looker or Looker Studio); building metric layers and stakeholder views
• Product analytics (Amplitude or Mixpanel) and UTM/event instrumentation
• Experimentation literacy (A/B testing design, power, confidence, false discovery awareness)
• CRM familiarity (Salesforce or HubSpot) and pipeline metric definitions
• Strong data storytelling: structuring insights for executives and cross-functional teams

Preferred experience (experimentation frameworks, CDP/ETL, marketing mix modeling, BI governance)

Use these as nice-to-haves, not gatekeepers.

• Python or R for data wrangling, forecasting, or experimentation analysis
• CDP/ETL tools (Segment, RudderStack, Fivetran, dbt) and event schema governance
• MMM, GeoLift, or causal inference frameworks for incrementality
• Looker semantic layer modeling and governance (explores, PDTs, access controls)
• B2B SaaS metrics (pipeline stages, opportunity hygiene, ARR, NRR) or B2C PLG funnels
• Privacy and consent management (GDPR/CCPA basics) in marketing analytics

Leveling guidance: Junior, Mid, Senior/Lead marketing analyst

Clarify expectations by level to reduce misalignment and support pay transparency.

• Junior: Executes defined analyses and dashboards; SQL for defined queries; learns experimentation basics; close mentorship.
• Mid: Owns a domain (paid performance, funnel, lifecycle); writes performant SQL; designs/reads A/B tests; drives stakeholder adoption.
• Senior/Lead: Sets analytics roadmap; mentors others; designs attribution/experimentation strategy; partners with Exec/Finance; influences budget and GTM strategy.

Compensation and benefits (pay transparency best practices)

Post a range tied to level and location; state variables clearly.

• Compensation range (example): $95,000–$140,000 base + bonus/equity, depending on level, experience, and location
• Benefits: medical, dental, vision; 401(k) or pension; paid parental leave; learning stipend; WFH setup; flexible PTO
• Note: We publish location-based ranges to comply with applicable laws (e.g., CA, CO, NY, WA) and benchmark via reputable market data. Final offer reflects experience, leveling, and geographic bands.

Location and work policy (remote/hybrid/on-site) and time zones

Be explicit to increase qualified apply clicks and reduce late-stage friction.

• Work policy: Remote-first within [countries/regions]; optional hybrid in [city]
• Collaboration hours: Core hours [e.g., 10:00–14:00 ET]; flexible outside of that
• Visa: [State if you sponsor or not]; right-to-work required in [countries]
• Travel: [e.g., Quarterly team onsites]

EEO, DEI, and inclusive language checklist

Use inclusive language and a clear EEO statement to widen your pipeline.

• Avoid gendered or exclusionary terms; focus on outcomes over personality traits
• Separate “required” from “preferred” to reduce self-selection bias
• Include accommodations language and invite applicants who meet most, not all, requirements
• EEO statement example: We’re an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic. We provide reasonable accommodations upon request.

Application instructions and timeline (ATS link, what to submit, process overview)

Tell candidates exactly how to apply and what to expect.

• Apply via ATS: [Direct link]; include resume/CV and one work sample (dashboard or analysis summary)
• Optional: brief note on a KPI you’ve improved and how you measured it
• Process: Recruiter screen → Technical exercise (SQL + analysis or live case) → Panel interviews → Final chat
• Timeline: We aim to respond within 5 business days; target start date [month]

JSON-LD JobPosting Structured Data: Implementation Example

Decide on one canonical version of the role and add structured data to increase discoverability. Structured data helps search engines index and display your role, improving discoverability and consistency.

Add JobPosting schema to your post and validate it before publishing. If your Careers page also lists the role, align canonical and schema to avoid duplication and ranking conflicts. Including JobPosting schema JSON-LD on your blog post also improves clarity for job aggregators that parse structured data.

Required vs recommended properties for JobPosting

Use required and strongly recommended fields to qualify for rich results and to keep job boards happy.

• Required: @context, @type, title, description, hiringOrganization.name, datePosted, employmentType, jobLocation or jobLocationType, validThrough, identifier
• Strongly recommended: hiringOrganization.logo and sameAs, baseSalary (range, currency, unitText), directApply, url, industry, occupationalCategory, applicantLocationRequirements (for remote), inLanguage, educationRequirements, experienceRequirements, skills

Copy-paste JSON-LD example for this role‍

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "JobPosting",
  "title": "Marketing Analyst",
  "description": "We’re hiring a Marketing Analyst to turn multi-channel and product data into actionable growth decisions. You’ll own acquisition and funnel analytics across GA4/BigQuery, paid channels, and the CRM, improving attribution and informing budget, experimentation, and forecasting.",
  "identifier": {
    "@type": "PropertyValue",
    "name": "YourCompany",
    "value": "MARKETING-ANALYST-2025-01"
  },
  "hiringOrganization": {
    "@type": "Organization",
    "name": "YourCompany",
    "sameAs": "https://www.yourcompany.com",
    "logo": "https://www.yourcompany.com/static/logo.png"
  },
  "industry": "Software | SaaS",
  "occupationalCategory": "15-2051.00",
  "employmentType": "FULL_TIME",
  "datePosted": "2025-12-13",
  "validThrough": "2026-01-31T23:59:00-05:00",
  "jobLocationType": "TELECOMMUTE",
  "applicantLocationRequirements": {
    "@type": "Country",
    "name": "United States"
  },
  "jobLocation": [{
    "@type": "Place",
    "address": {
      "@type": "PostalAddress",
      "addressLocality": "Remote",
      "addressRegion": "US",
      "addressCountry": "USA"
    }
  }],
  "baseSalary": {
    "@type": "MonetaryAmount",
    "currency": "USD",
    "value": {
      "@type": "QuantitativeValue",
      "minValue": 95000,
      "maxValue": 140000,
      "unitText": "YEAR"
    }
  },
  "directApply": true,
  "url": "https://www.yourcompany.com/careers/marketing-analyst",
  "inLanguage": "en-US",
  "educationRequirements": "Bachelor’s degree or equivalent practical experience",
  "experienceRequirements": "2+ years in marketing/product analytics with SQL",
  "skills": "SQL, GA4, BigQuery, Looker/Looker Studio, A/B testing, Amplitude/Mixpanel"
}
</script>

SEO for a Job Posting on Your Company Blog

Treat your posting like a landing page to match intent and convert. When publishing a marketing analyst job posting in technology company blog context, optimize for candidate intent and ensure your blog doesn’t compete with your Careers site. Use on-page best practices, canonical alignment, and tracking so you can attribute qualified applies.

Choose one indexable, canonical URL to avoid internal competition. If your Careers page is the system of record, set that as canonical and keep the blog post as a narrative overview pointing to apply. Alternatively, host the full posting on the blog and noindex the duplicate ATS page if possible. The goal is one indexable URL with complete details, valid schema, and strong internal links.

On-page essentials: title tags, meta description, H1/H2s, internal links to Careers and Team pages

Hit the basics that improve relevance and crawlability.

• Title tag: “Marketing Analyst Job Posting (Tech) | [Company] Careers”
• Meta description: Include role, stack (SQL, GA4), location/remote, and the apply CTA
• H1: Clear role + company type; H2s that match candidate questions (responsibilities, requirements, benefits)
• Internal links: Careers hub, Team/About, Engineering/Data blog posts, and relevant culture pages
• Include “marketing analyst job posting,” “marketing analyst job description,” and related terms naturally

Canonicalization with Careers pages and handling expiry/updates

Avoid duplicate content and keep freshness signals strong.

• If role exists on Careers/ATS, set the Careers URL as canonical; link prominently from the blog to apply
• Update “datePosted” and “validThrough” in schema when extending or closing roles
• When the role closes: remove apply links, add “Closed” notice, set noindex or 410, and redirect to Careers hub or talent community
• Maintain a single source of truth for the posting content; keep schema in sync

Tracking: UTMs for distribution and goal setup for apply clicks

Measure what matters so you can scale channels that work.

• Use UTMs on every distribution link: utm_source, utm_medium, utm_campaign, utm_content for creative/test
• Create GA4 events for apply clicks (e.g., “apply_click”) with event parameters (source, job_id)
• Track conversions in ATS by source; pass UTMs through redirectors and ensure they persist to the apply URL
• Build a Looker/Looker Studio dashboard mapping sessions → apply clicks → completed applications

Distribution Playbook: From Your Blog to Qualified Applicants

Prioritize owned channels, then layer targeted communities and selective paid boosts. Distribute beyond LinkedIn to reach analytics talent where they are. Use owned channels first for speed and authenticity, then layer niche communities and selective paid boosts. Always tag links with UTMs and coordinate with your Talent Partner to attribute candidates in your ATS.

Align title and messaging to audience expectations to pre-filter candidates. Align messaging to the title you chose (Marketing Analyst vs Digital/Growth Analyst) to match audience expectations. Include the stack (SQL, GA4, Looker) and outcomes (CAC/LTV, experimentation) in your social copy to filter in the right applicants.

Owned channels: LinkedIn company page, employee advocacy, newsletter, Slack/Discord communities

Amplify to warm audiences who already trust your brand.

• LinkedIn company post + employee reshares with tailored captions
• Personal posts from hiring manager with 1–2 bullets on outcomes and stack
• Company newsletter slot and career/culture blog cross-links
• Relevant Slack/Discord communities (e.g., MarketingOps, RevOps, Product-Led Growth) following community rules

Niche boards and communities for analytics/tech talent

Target communities tuned to marketing and product analytics.

• Analytics and data communities (e.g., r/analytics, Women in Analytics, Black in Data)
• Growth and PLG communities (e.g., GrowthHackers, Product-Led Growth community)
• MarketingOps/RevOps forums and job channels
• Wellfound (AngelList), HN “Who’s Hiring” (if engineering overlap), local tech hubs

ATS integration tips and tracking conversions by source

Close the loop between marketing and recruiting ops.

• Use a single ATS requisition with source tracking; generate campaign links per channel
• Map UTM source/medium to ATS source fields; test end-to-end before launch
• Configure webhooks or nightly exports to your warehouse for dashboarding
• Align on weekly reporting: impressions → clicks → completed applies → interview rate → offer rate by channel

Assessment: Screening Checklist and Interview Rubric

Standardize screening and interviews to improve signal and reduce bias. Calibrate the bar to your leveling and stage, and evaluate storytelling as highly as SQL. Share the rubric with interviewers and hold a brief pre-brief to anchor expectations.

Make the scorecard mirror the job so you hire for impact, not trivia. Scorecards should map to responsibilities and KPIs in the posting. Prioritize evidence of shipped work that changed outcomes (e.g., budget reallocation from an attribution analysis) over tool trivia.

Resume and portfolio screening signals (SQL/experimentation/data storytelling)

Look for shipped outcomes and stack alignment.

• SQL depth: joins, window functions, query optimization; examples in resume/portfolio
• GA4 + BigQuery, Looker/Looker Studio, and one product analytics tool
• A/B testing ownership: hypothesis, design/power, analysis, decisions made
• Attribution and funnel work that connected to pipeline/revenue and influenced budget
• Clear artifacts: dashboards, PRDs for tracking, documentation links

Take-home or live exercise ideas with evaluation criteria

Assess practical skill fairly and time-box to 60–90 minutes.

• SQL + analysis: Provide simplified BigQuery schema (sessions, events, campaigns, CRM stages); ask for funnel metrics and test-readout
• Experiment critique: Share an anonymized A/B test; ask for interpretation, pitfalls, and next steps
• Data storytelling: Candidate presents a short analysis; evaluate structure, clarity, and business impact
• Evaluate on correctness, approach, communication, and tradeoff awareness—not just final numbers

Behavioral and cross-functional collaboration questions

Test for stakeholder alignment and bias toward impact.

• Tell me about an analysis that changed a budget or roadmap. How did you persuade stakeholders?
• Describe a time tracking was unreliable. How did you diagnose and fix it?
• How do you decide when to run an experiment vs. ship based on directional data?
• How do you balance speed vs. rigor when executives want an answer quickly?

Compliance and Risk: Pay Transparency, EEO, and Global Hiring Notes

Decide compliance up front to build trust and avoid rework later. Compliance builds trust and protects your brand. Many jurisdictions now require salary ranges, and inclusive, bias-aware language expands your qualified pipeline.

Coordinate with Legal/HRBP on jurisdictional requirements and your global hiring policies before publishing. Eliminate surprises by stating eligibility and location rules clearly. Use clear visa/eligibility statements up front to avoid late-stage surprises. For remote roles, disclose eligible countries/regions and whether you support employer-of-record solutions.

Pay transparency laws (state/country nuances) and best practices

Stay ahead of evolving laws and candidate expectations.

• Publish base salary range and variable/equity details where applicable (e.g., CO, CA, NY, WA in the U.S.)
• Note location-based pay bands and how they apply to remote roles
• Avoid asking for salary history; focus on range and leveling
• Link to your compensation philosophy if public; keep ranges updated when market data changes

Visa sponsorship and right-to-work statements

Set expectations clearly for global candidates.

• State sponsorship availability (e.g., “We can/cannot sponsor work visas for this role”)
• List eligible hiring countries or regions and any time-zone constraints
• Include right-to-work requirement and accommodations for relocation where applicable
• If using EOR/PEO partners, specify which countries are supported

Publishing Governance for Job Posts on a Blog

Run hiring posts through a clear workflow so content stays accurate and compliant. Treat hiring posts as product content with owners and a lifecycle. Define who writes, who approves, and how posts are updated or sunset to keep your site accurate and trustworthy.

Use a simple, repeatable workflow to reduce errors and delays. A simple workflow reduces errors: draft → legal/compliance check → SEO/schema validation → publish → track → review.

Update cadence, sunset/expiry rules, and redirects

Keep your hiring content fresh and user-friendly.

• Review open roles weekly; update “datePosted,” “validThrough,” and apply links
• Close roles by removing apply CTAs, adding a status note, and noindexing or redirecting
• Redirect closed roles to Careers hub or talent community to preserve link equity
• Maintain a changelog for compliance updates and compensation range changes

Who approves what: Hiring manager, recruiter, legal/HRBP

Assign clear ownership to move fast without risk.

• Hiring manager: role scope, responsibilities, KPIs, interview rubric
• Recruiter/Talent: leveling, compensation bands, process and timeline, ATS setup
• Legal/HRBP: pay transparency, EEO language, visa/right-to-work statements, jurisdictional compliance
• SEO/Web: schema validation, canonical/robots, analytics and UTM consistency

FAQs

• What’s the difference between a Marketing Analyst, a Digital Marketing Analyst, and a Growth Analyst—and which title should I use?
• Use Marketing Analyst for broad funnel and revenue analytics across channels and product. Use Digital Marketing Analyst when the role is primarily channel/web-focused. Use Growth Analyst when experimentation and product data (SQL-heavy) dominate the scope.
• Which responsibilities and KPIs should a tech-focused Marketing Analyst own at different stages?
• Early-stage: tracking setup, foundational dashboards, basic experiments. Growth-stage: attribution strategy, A/B testing at scale, budget recommendations. Enterprise: governance, MMM/incrementality, mentorship, and cross-org frameworks. KPIs: pipeline/revenue, CAC/LTV, attribution quality, test velocity, and funnel conversion.
• Which tools are must-have vs nice-to-have?
• Must-have: SQL, GA4 with BigQuery, BI (Looker/Looker Studio), product analytics literacy, and experimentation basics. Nice-to-have: Python/R, advanced attribution/MMM, CDP/ETL (Segment/Fivetran/dbt), and Looker modeling.
• How do I add JSON-LD JobPosting schema and avoid conflicts with our Careers page?
• Add the JSON-LD snippet to the blog post, but set the canonical to the Careers URL if both pages exist. Ensure only the canonical page is indexed and both schema and content match. Update datePosted/validThrough as the role status changes.
• How do I handle pay transparency and location-based ranges for remote roles?
• Publish a range with a note on location-based bands. Provide separate ranges or a wide band and clarify factors (experience, level, geography). Avoid salary history questions and keep the range current.
• What inclusive language guidelines should we follow?
• Avoid gendered terms and over-indexing on “rockstar/ninja.” Separate required vs preferred skills, invite applicants who meet most requirements, and include accommodations and a clear EEO statement.
• What screening checklist and interview rubric should we use?
• Screen for SQL, GA4/BigQuery, BI, experimentation, and storytelling with shipped outcomes. Use a time-boxed SQL + analysis task, an experiment critique, and a short presentation with a clear scoring rubric.
• How should we structure application instructions to increase qualified applies?
• Link directly to the ATS, ask for a resume and a relevant work sample, outline the process and timeline, and include eligibility notes. Keep the apply button prominent and repeat CTAs.
• Which channels beyond LinkedIn deliver qualified applicants?
• Analytics and growth communities (e.g., r/analytics, Women in Analytics, MarketingOps/RevOps groups), Wellfound, and local tech hubs. Encourage employee referrals with trackable links.
• How do we track performance (UTMs, conversions, attribution)?
• Use UTMs on every link, GA4 events for apply clicks, ATS source mapping, and a dashboard tying sessions → applies → interviews → offers by channel.
• When should we use canonical tags or de-index a job post after it closes?
• If Careers is the source of truth, canonicalize to it while the role is open. When closed, remove CTAs, add a notice, and noindex or 410/redirect to Careers hub or talent community.
• What visa sponsorship and right-to-work statements should be included?
• Explicitly state sponsorship availability, eligible countries/regions, time zones, and right-to-work requirements. If you use EOR/PEO partners, list supported countries.

Summary and Downloadables

You now have a tech-ready marketing analyst job posting, schema markup, and a publishing plan to reach qualified candidates quickly. Ship the role with the template above, implement the JSON-LD JobPosting example, and follow the SEO, distribution, and assessment checklists for consistent results.

• Copy-paste assets:
• Job posting template sections (Role Summary, Responsibilities by stage, Required/Preferred, Compensation, EEO, Application)
• JSON-LD JobPosting snippet for immediate implementation
• Next steps:
• Align on title and scope (Marketing vs Digital vs Growth Analyst)
• Publish with canonical/UTMs, validate schema, and launch distribution
• Use the screening checklist and rubric to interview with confidence

If you’re optimizing for company blog job posting SEO, revisit this guide each time you open a role to keep compliance, schema, and process tight.