GTM Data Engineer & Automation in Brighton

GTM Data Engineer & Automation in Brighton

Brighton Full-Time 45000 - 55000 £ / year (est.) On-site
NYLON

At a Glance

  • Tasks: Own the data layer and ensure clean prospect data for AI tools.
  • Company: Nylon, a forward-thinking company revolutionising legal and accounting sectors.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on cutting-edge technology.
  • Why this job: Join a dynamic team and make a real impact with innovative AI solutions.
  • Qualifications: Experience in data engineering and automation, with strong problem-solving skills.

The predicted salary is between 45000 - 55000 £ per year.

Nylon is building AI research tools for lawyers and accountants across NZ, AU and the UK.

We’re hiring a GTM Engineer to own the data layer, ensuring clean prospect data, reliable CRM integrations and scalable automation.

You’ll be hands-on at the intersection of sales operations, data and automation, working with Attio, Just Call, Calendly, Stripe and Metabase to connect the stack and deliver trusted insights for growth.

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GTM Data Engineer & Automation in Brighton employer: NYLON

At Nylon, we pride ourselves on being an innovative employer that empowers our team members to drive meaningful change in the legal and accounting sectors. As a GTM Engineer, you'll enjoy a collaborative work culture that values data-driven decision-making and offers ample opportunities for professional growth, all while working with cutting-edge AI tools in a dynamic environment across New Zealand, Australia, and the UK. With no legacy systems to hinder your creativity, you will have the freedom to implement solutions that directly impact our success and shape the future of our platform.

NYLON

Contact Details:

NYLON Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land GTM Data Engineer & Automation in Brighton

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like NYLON!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like GTM Data Engineer & Automation at NYLON.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like NYLON.

✨Apply Directly through Our Website

When you find a suitable opening like GTM Data Engineer & Automation at NYLON, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace GTM Data Engineer & Automation in Brighton

Data Management
CRM Integration
Automation
Sales Operations
Data Analysis
Metabase
Attio

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at NYLON, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at NYLON. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at NYLON

✨Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

✨Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at NYLON!

✨Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.