Data Engineer & Analytics Lead

Neosurf
Woking
1 month ago
Applications closed

Related Jobs

View all jobs

Data Engineer / Analytics Engineer

Senior Data Engineer

Data Architect

Data Engineer

Data Engineer

Data Engineer

Get AI-powered advice on this job and more exclusive features.

Neosurfis on the lookout for a passionate and highly skilledData Engineer & Analytics Leadto join our growing team! This is an exciting opportunity to revolutionise how we use data to drive business decisions, enhance user experiences, and stay ahead in the fast-paced world of online payments. If you’re a data whizz with a knack for leadership, a love for solving complex problems, and a desire to make a real impact, this role is for you!

The Role

As our Data Engineer & Analytics Lead, you'll be the driving force behind our data strategy, responsible for building, optimising, and leading our data infrastructure. You will be instrumental in designing and implementing data pipelines, developing insightful visualisations, and mentoring a team of data professionals. This is a hands-on role that requires both technical expertise and leadership skills, as well as someone who's not afraid to roll up their sleeves and delve into the details. You will have the autonomy to recommend and lead improvements to our data systems, processes and to champion best practices across the business.

You'll spend your time:

  • Designing, building, and maintaining our data warehouse (Snowflake).
  • Developing and optimising ETL processes for seamless data integration.
  • Creating compelling data visualisations and dashboards using Power BI.
  • Performing in-depth data analysis to uncover actionable insights and identify opportunities for growth and improvement.
  • Leading and mentoring a team of data analysts, fostering a culture of collaboration and continuous learning.
  • Identifying and implementing process improvements through automation of data pipelines.
  • Ensuring data quality and integrity across all systems.
  • Collaborating with cross-functional teams (product, marketing, finance) to understand their data needs and provide tailored solutions.
  • Staying up-to-date with the latest trends and technologies in data engineering and analytics.
  • Exploring the application of machine learning techniques to solve business challenges.
  • Being a champion for data-driven decision-making across the company.

Key Skills & Experience

  • Proven experience as a Data Engineer and Analyst, with a strong understanding of the full data life cycle.
  • Deep expertise in data warehousing concepts and technologies, particularly Snowflake.
  • Expertise in SQL, Python and other data manipulation and scripting languages.
  • Excellent data visualisation skills, with experience using Power BI or Tableau.
  • CRM skills experience, preferably Salesforce.
  • Strong understanding of ETL processes and data transformation techniques.
  • Solid experience in data analysis, with the ability to extract actionable insights from complex datasets.
  • Experience in leading and coaching a team of data professionals.
  • A passion for data quality, accuracy and attention to detail.
  • Excellent communication and presentation skills, with the ability to convey technical concepts to non-technical audiences.
  • Experience in identifying and implementing process improvements through automation.
  • Experience in the payments, regulatory or financial industry.
  • Familiarity with machine learning techniques and tools.
  • Knowledge of data governance principles and practices.
  • Understanding of marketing analytics techniques, such as segmentation and funnel analysis.

What We Offer

  • A competitive salary and benefits package.
  • A dynamic and innovative work environment.
  • Opportunities for professional growth and development.
  • The chance to work on exciting projects that make a real impact.
  • A supportive and collaborative team culture.
  • Flexible working arrangements.
  • Company pension scheme.
  • Private medical insurance and additional well-being scheme.
  • Regular social events and team-building activities.

Diversity and Equality Employment

At Neosurf, we embrace diversity and foster a work environment built on mutual respect. As an equal opportunity employer, we value individuals from all walks of life, regardless of race, colour, religion, national origin, age, gender identity or expression, or any other protected characteristic.

Please complete the questions, provide a copy of your CV and a cover letter outlining your relevant experience and why you're the perfect fit for this role.

We look forward to hearing from you.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Information Technology

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Jobs

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Jobs Careers

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.