Data Architect

Gallagher
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Analyst - Performance

Data Engineer (AI Analytics and EdTech Developments)

Data Engineer DV Cleared

Senior Data Engineer (Microsoft Fabric)

Data Engineer

Overview

At Gallagher Re, we are seeking an experienced Data Architect to join our gloabl technology team. As our Data Architect, you will contribute to the architecture and implementation of our data strategies using Snowflake and Azure. You will be responsible for developing data solutions that are scalable, efficient, and optimized to meet our business needs and we continue to grow. How you'll make an impact Design and develop data models for large-scale databases on the Azure platform & Snowflake, ensuring scalability, performance, and data integrity. Collaborate with stakeholders, including data analysts, developers, and business analysts, to understand data requirements and translate them into effective data models. Assess database implementation procedures to ensure they comply with internal and external standards. Implement best practices for data modeling, including normalization, denormalization, indexing, and partitioning strategies. Prepare accurate database design and architecture reports for management and executive teams. Oversee the migration of data from legacy systems to cloud solutions. Stay up-to-date with the latest trends and advancements in data modeling techniques, tools, and technologies. Document data models, data dictionaries, and related artifacts to facilitate knowledge sharing and maintain data lineage. About You Degree obtained in Computer Science, Information Systems, or a related field. Proven experience as a Data Architect. Knowledge of data modeling concepts, techniques, and best practices. Proficiency in SQL and experience with database management systems (DBMS) such as Azure SQL Database, Azure Synapse Analytics, or Azure Cosmos DB. Hands-on experience with Azure services, including Azure Data Factory, Azure Data Lake Storage, and Azure Databricks. Familiarity with data integration and ETL processes, including data ingestion, transformation, and loading. Experience with Snowflake. Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams. Compensation and benefits On top of a competitive salary, great teams and exciting career opportunities, we also offer a wide range of benefits. Below are the minimum core benefits you’ll get, depending on your job level these benefits may improve: Minimum of 25 days holiday, plus bank holidays, and the option to ‘buy’ extra days Defined contribution pension scheme, which Gallagher will also contribute to Life insurance, which will pay 4x your basic annual salary, which you can top-up to 10x Income protection, we’ll cover up to 50% of your annual income, with options to top up Health cash plan or Private medical insurance Other benefits include: Three fully paid volunteering days per year Employee Stock Purchase plan, offering company shares at a discount Share incentive plan, HMRC approved, tax effective, stock purchase plan Critical illness cover Discounted gym membership, with over 3,000 gyms nationally Season ticket loan Access to a discounted voucher portal to save money on your weekly shop or next big purchase Emergency back-up family care And many more…

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.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 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.