Head of Sales Europe (Remote Europe)

N8n GmbH
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Data Analyst - Farming Operations

Head of Data Architecture

Head of Data Compliance

Head of Data Science

Head of Data Analytics

This job is brought to you by Jobs/Redefined, the UK's leading over-50s age inclusive jobs board.

Please ensure you read the below overview and requirements for this employment opportunity completely.n8n is a workflow automation platform that uniquely combines AI capabilities with business process automation. We give technical teams the flexibility of code with the speed of no-code, backed by a passionate community of builders. With 400+ integrations and fair-code principles, we're revolutionizing how businesses connect their systems and processes.

We were founded at the end of 2019 and currently:

We're a diverse team of +70 talented people.

Our annual recurring revenue is growing 3x year-over-year.

With +51k GitHub stars, we are in the top 0.0001% most popular projects on GitHub.

We're Europe's 25th fastest growing startup in 2024 according to Sifted.

We now count a total of $20m in funding: we were Sequoia's first seed investment in Germany, and most recently secured a Series A extension (February 2024).

MISSIONS

Your main goal will be to lead, empower, and support a team of high-performing Sales Development Representatives (SDRs) and Account Executives (AEs), driving customer acquisition and growth globally.

To do so, here are your responsibilities:

Coaching & developing Account ExecutivesProvide strategic coaching and mentorship to help SDRs and AEs consistently hit and exceed their targets.Foster career growth, helping AEs push for promotions and develop their sales skills.Lead by example, creating a positive, high-performance culture within the team.

Sales EnablementEnsure AEs and SDRs have the tools, resources, and training needed to succeed, from onboarding new hires to ongoing sales development.Collaborate with cross-functional teams (Marketing, RevOps, Sales Enablement) to optimize resources and materials that enable successful selling.Drive continuous improvement in our sales approach by refining the playbook and processes.

Pipeline managementOversee and manage the pipeline to ensure 4x coverage for the upcoming quarter.Provide strategic guidance on pipeline generation, qualification, and progression to maximize opportunities.Collaborate with SDRs and Solutions Engineers to ensure a steady flow of quality leads and technical support.

Sales process optimisationContinuously optimize sales processes to improve efficiency and productivity across the team.Leverage data and insights to refine sales strategies, ensuring we stay agile in a fast-growth environment.Work closely with the VP Sales and RevOps Lead to ensure accurate sales forecasting and reporting.

Reporting & forecastingMaintain strong operational rigour with accurate forecasting (within 10% accuracy) and regular reporting on sales performance.Use data-driven insights to track team performance, adjust strategies, and ensure revenue targets are met and exceeded.Ensure that the sales team is on track for long-term growth and development by setting clear goals and tracking progress.

The go-to-market team:

VP Sales

1 SDR

3 Solutions Engineers

2 Mid-Market Account Executives

3 Enterprise Account Executives

1 Customer Success Engineering Lead

1 Head of Revenue Operations

1 Senior Data Analyst (GTM)

Upcoming hires:

Sales Enablement, Accounts Executives, Team Lead SDR, SDRs.

Requirements

Must-have

Sales Leadership Experience:

You have at least 3 years of experience managing a team of New Business Account Executives (no personal quota).

Selling to Mid-Market & Enterprise:

You are experienced in managing sales teams selling deals at least in the €30-100k range to medium and large companies (500+ employees).

High-Growth Experience:

You've been part of a high-growth BtoB SaaS tech company and thrive in a fast-paced, constantly evolving environment (x2 yoy).

Technical Sales Experience:

You have experience selling a technical product or selling to a technical persona, or a technical background yourself.

Market Knowledge:

You have a deep understanding of EMEA markets and the nuances of selling across this diverse region.

Nice-to-have

Experience Managing Remote Teams:

You've successfully managed sales teams working remotely across international markets.

Larger Deal Experience:

You've managed AEs working on deals in the €100k-500k range.

Renewals & Upgrades Experience:

You've led teams responsible for handling renewals and upgrades in addition to new business.

PLG/PLS Sales Motion:

You're familiar with Product-Led Growth or Product-Led Sales motions and how they integrate into an outbound sales approach.

Outbound Sales Expertise:

You've built and managed teams that have developed outbound sales motions.

n8n is an equal opportunity employer and does not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status.

We can sponsor visas to Germany; for any other country, you need to have existing right to work.

Our company language is English.

You care about diversity and inclusion? We do too! Check out our Diversity, Inclusion and Belonging initiatives at n8n (https://www.notion.so/n8n/Diversity-inclusion-and-belonging-n8n-c1bec2ff...).

Location disclaimer:

If you see multiple job postings for the same role, it is most likely because we're hiring remotely for this role and posting in different locations to make sure every potential candidate can see the role. Please apply to the location you're the most likely to work from in the future.

Benefits

Competitive compensation

Ownership:

Our core value is to "empower others", and we give you a slice of n8n in the form of equity.

Work/life balance:

We work hard, but make sure everyone can properly recharge their batteries with 30 days holiday, plus public holidays wherever you are.

Career growth:

We are looking to hire 'rising stars', who can grow with the company into more senior roles. We give you €1k a year to spend on courses, books, events and coaching, to support you in developing your career.

A passionate team:

We love our product, and we have regular office hackathons to see who can build the coolest thing with it!

Remote-first:

Unless specified otherwise on the job posting, our team works remote from anywhere within Europe but we have regular off-sites to help build team bonds and alignment.

Transparency:

We all know what everyone's working on, how's the company doing - the whole shebang.

Giving back:

We're big fans of open source, and you'll get $100 per month to support projects you care about.

Ambitious but kind culture:

where people love to work - our eNPS for 2023 is 100!

#J-18808-LjbffrRemote working/work at home options are available for this role.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.