Senior Marketing Data Analyst at N26

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• 🏢 N26 has 139 jobs here, 136 with visa sponsorship see all
• 🛂 Visa: Highly Qualified Professional permit. Education: Higher education degree guide
• 💡 No salary shown. Ask N26 if it is above the minimum.

Updated 2026-11-05, from our data and official sources.

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About the role

Responsibilities:
- Lead the Acquisition Measurement domain: define and own roadmap, prioritise work with business and technical stakeholders.
- Act as primary analytics partner to acquisition teams (Paid Media, Strategy, Referrals, Product Marketing) on measurement and data questions.
- Drive Marketing Science initiatives: collaborate on Marketing Mix Modeling, promote Customer Lifetime Value usage, and own Test & Learn experiments end-to-end (design, analysis, share-outs).
- Build scalable, self-serve resources: define measurement frameworks, design/maintain analytics dashboards, and establish reliable data-model lineage.
- Communicate insights and enable teams: document findings, create playbooks, run knowledge-sharing sessions to raise analytics maturity.
- Contribute to OKRs and align measurement to business goals; collaborate across analytics community.

Requirements:
- 5+ years in Marketing or Product Analytics with a clear focus on acquisition strategy and performance measurement.
- Strong SQL and Python or R skills; experience with BI tools (Looker/Tableau/Metabase/Superset) and data modeling.
- Hands-on experience with Marketing Mix Modeling and experimentation (A/B test design and analysis).
- Solid understanding of statistical methods, hypothesis testing, audience segmentation, and conversion rate optimization.
- Ability to translate complex analyses into clear recommendations for non-technical stakeholders and influence senior leadership.
- Collaborative, documentation-minded, and experienced working in cross-functional teams.

Responsibilities

Lead the Acquisition Marketing Measurement roadmap to enable data-driven decisions and foster a culture of continuous improvement. Collaborate with cross-functional teams to build scalable analytics dashboards and drive Marketing Science initiatives like Marketing Mix Modeling.

Requirements

Requires over 5 years of experience in Marketing or Product Analytics with a strong background in experimental design and statistical methods. Proficiency in SQL, Python/R, and data visualization tools is essential for translating complex analysis for non-technical stakeholders.

Key skills

• SQL — in 545 other listings on The Stack
• Python — in 1200 other listings on The Stack
• R — in 45 other listings on The Stack
• Tableau — in 65 other listings on The Stack
• Looker — in 44 other listings on The Stack
• Metabase — in 22 other listings on The Stack
• Superset — in 18 other listings on The Stack
• Marketing Mix Modeling — in 4 other listings on The Stack
• Experimental Design
• Hypothesis Testing
• Data Storytelling
• Data Visualization
• Audience Segmentation
• Conversion Rate Optimization
• Data Modeling
• Customer Lifetime Value

On The Stack (as of 2026-11-05)

• N26 has 138 other listings on The Stack, 135 of them marked as offering visa sponsorship.
• 76 visa-sponsored jobs in Spain on The Stack, posted in the last 60 days.
• 24 visa-sponsored data analyst jobs in Europe on The Stack, posted in the last 60 days.

Frequently asked questions about N26

Is this Senior Marketing Data Analyst role still open?

It was posted on 2026-07-03. Listings more than 30 days old may no longer be active, so check N26's site before applying.

Does N26 offer visa sponsorship?

This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on N26's site.

Where is this role located?

The listing gives the location as Spain. It is marked on-site.

What skills does this role ask for?

The listing names: SQL, Python, R, Tableau, Looker, Metabase, Superset, Marketing Mix Modeling, Experimental Design, Hypothesis Testing, Data Storytelling, Data Visualization, Audience Segmentation, Conversion Rate Optimization, Data Modeling, Customer Lifetime Value.