Manager Data Engineer - D&ET - Technology Consulting - Belfast & Derry/Londonderry

EY
Belfast
2 weeks ago
Create job alert

Manager Data Engineer - Digital & Emerging Technologies - Technology Consulting - Belfast & Derry/Londonderry At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we're counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. The opportunity This is a rapidly growing area, so you will have plenty of opportunity to spread your wings and develop your skill set to keep up with the ever-growing demands of the digital landscape. Our Data Services Group team helps apply cutting edge technology and techniques to bring solutions to our clients. As part of that, you'll sit side-by-side with clients and diverse teams from EY and we'll look to you to provide our clients with a unique business perspective on how they must continue to innovate and remain competitive in this ever-changing industry. We are seeking individuals with significant client-side and people management experience, who have gained project and technology delivery experience within large recognised organisations. Your key responsibilities Participate in presentations and proposals for medium complex projects or elements of highly complex projects Logical and physical data modelling - Design, develop, and maintain data pipelines and models Assists in data modelling and design reviews, striving for improved usability and efficiency Implements code for data extraction and basic transformations Validates data quality and maintains source control and versioning Contributes to data tool development and platform monitoring Writing SQL scripts and stored procedures, optimize and tune SQL queries for performance and efficiency Design, implement and maintain data security and access controls. Troubleshoot and resolve data-related issues Agile management and scrum master, maintaining roadmap, tasks, and making sure everyone in the team is working towards a clear goal To qualify for the role, you must have 5+ year(s) experience in business analytics, data science, software development, data modelling or data engineering Good understanding of scripting Excellent SQL, preferably T-SQL, development skills. Experience in data wrangling and standard data cleansing, in different formats, including CSVs and structured tables. Good understanding with Microsoft BI toolset, including O365 tools and PowerPlatform (PowerApps/Power Automate/Power BI). Good understanding of Azure cloud ETL toolset, including Azure SQL Server, Azure Data Factory, Datalake. Familiar with Cloud technologies including Microsoft Azure Cloud infrastructure, data stores connections, cloud functions concepts. Experience in programming languages like Python, Java, or C#. Experience in cloud data platforms like Snowflake, Databricks or Azure Synapse. Good understanding of Data Modelling techniques. Ideally, you'll also have Relevant academic background Participation in the opensource community Expertise in automation and/or digital transformation Certification in MS Azure or AWS Cloud data engineering or similar track Understanding of the Software Development Life Cycle, Devops and MLOPS Strong skills in one object orientated language Excellent presentation skills Understanding application of project mgmt. and agile methodologies What we look for We're interested in candidates with a genuine creative vision and the confidence to make it happen. You can expect plenty of autonomy in this role, so you'll also need the ability to take initiative and seek out opportunities to improve our current relationships and processes. If you're serious about auditing and ready to take on some of our clients' most complex issues, this role is for you. What we offer Continuous learning: You'll develop the mindset and skills to navigate whatever comes next. Success as defined by you: We'll provide the tools and flexibility, so you can make a meaningful impact, your way. Transformative leadership: We'll give you the insights, coaching and confidence to be the leader the world needs. Diverse and inclusive culture: You'll be embraced for who you are and empowered to use your voice to help others find theirs. If you can demonstrate that you meet the criteria above, please contact us as soon as possible. The exceptional EY experience. It's yours to build. Please note; Prior to finalizing your application, you will be asked to provide personal information across several dimensions of diversity and inclusiveness. The information you provide is kept entirely confidential and will not be used to evaluate your candidacy. We collect this data to help us analyse our recruitment process holistically and implement actions that promote diversity and inclusiveness. While optional, we encourage you to provide this information to hold us accountable towards our goal of building a better working world. Read more about our commitment to diversity& inclusiveness here . We ask because it matters! EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today. Tech To be considered for this role you will be redirected to and must complete the application process on our careers page. To start the process click the Apply button below to Login/Register.

Related Jobs

View all jobs

Delivery Manager - Data Engineering Platform

Program Manager

IT Project Manager

Senior Data Developer

Senior Data Engineering Manager

Data Engineering Manager

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.