Data Manager / Data Architect

ZipRecruiter
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Developer

Senior Data Engineering Manager

Data Governance Manager

Data Science Manager – Gen/AI & ML Projects - Bristol

Data Science Manager

Data Analyst - Graduate

Job Description

I'm recruiting for a passionate data leader to join a non-profit organisation in their London office - with 1-2 days per week on-site.

In this role you will take responsibility for leading the data pillar within the organisation, and will be the "face" of data within the Senior Leadership Team.

You will lead on the design and delivery of a data strategy and roadmap - encompassing data architecture, master data management, reporting and analytics, and even exploring the use of new technologies including AI.

In doing so, you will lead a small data team (including BI Developers, Data Engineers and Data Quality Specialists) to deliver exceptional solutions, whilst liaising with other departments across the organisation to ensure they're fit-for-purpose.

Their technology stack is Microsoft focused, including SQL, Azure, Power BI and D365, so we are looking for a good understanding of Microsoft data technologies.

This is a brilliant opportunity to really lead this organisation in levelling-up their data capabilities - whether you are already in a leadership role, or you're looking to take that next step-up in your career.

Requirements

  • Experience designing data strategies / roadmaps
  • Experience designing data solutions using Azure data platform technologies
  • Experience leading data teams or leading on the delivery of data projects
  • Knowledge of data governance frameworks and data quality best-practice
  • Knowledge of data visualisation tools
  • Knowledge of ML or AI techniques would be great
  • Excellent stakeholder engagement and relationship building skills

Benefits

  • Salary up to around £68,500 depending on experience
  • 25 days annual leave plus bank holidays (rising to 30 days with length of service)
  • Generous contributory pension scheme
  • Life assurance
  • Health cash plan
  • Enhanced maternity and shared parental leave contributions

#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.

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!

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.

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.