Data Architect - GCP - Contract

Norton Blake
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer DV Cleared

Data Analyst - Performance

Data Engineer (AI Analytics and EdTech Developments)

Data Analyst - Performance

Business Data Analyst

GCP Data Architect - Contract - Hybrid £750pd (inside IR35) (Potential Extensive Travel to Dubai) Position Overview: My client, a leader in their field are seeking an experienced GCP Data Architect for an exciting 6-month contract role, with the potential for extension. This position may require extensive travel to Dubai , making it a fantastic opportunity for someone who enjoys working internationally. The ideal candidate will have a deep understanding of Google Cloud Platform (GCP) and strong experience in designing and implementing complex data architectures . You will be instrumental in helping shape the data strategy, ensuring scalability, performance, and alignment with business objectives. Key Responsibilities: Data Architecture Design: Lead the design and implementation of scalable, secure, and efficient data architectures on GCP. Cloud Integration: Work closely with cloud infrastructure teams to ensure seamless integration between GCP and other enterprise systems. Big Data Solutions: Develop and implement data lakes, data warehouses, and real-time data processing pipelines using GCP services such as BigQuery, Dataflow, Pub/Sub , and Cloud Storage . Data Governance & Security: Implement best practices for data governance, privacy, and security, ensuring compliance with local regulations. Collaboration: Work cross-functionally with business, IT, and external stakeholders to gather requirements, and translate them into effective data solutions. Performance Optimization: Optimize data pipelines, queries, and data storage solutions to enhance performance and reduce costs. Data Strategy: Develop and execute data strategies aligned with long-term business objectives. Required Skills & Experience: Extensive experience as a Data Architect with a strong focus on GCP . Proven experience in designing and implementing cloud-based data solutions (data lakes, data warehouses, etc.). Deep understanding of GCP tools including BigQuery, Dataflow, Pub/Sub, Cloud Functions , and Cloud Storage . Strong knowledge of data modeling , ETL pipelines , and data governance . Experience with security practices and ensuring compliance with industry standards. Strong skills in SQL and Python for data processing. Ability to travel internationally, particularly to Dubai , as required. If you are a proactive, innovative GCP Data Architect with a passion for developing world-class data solutions, we encourage you to apply. GCP Data Architect - Contract - Hybrid - £750PD (inside IR35)

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.

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.

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.

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.