GCP Data Architect (Basé à London)

Jobleads
London
2 months ago
Applications closed

Related Jobs

View all jobs

Master Data Engineer

Data Engineer

GCP Data Engineer (Java, Spark, ETL)

GCP Data Engineer (Java, Spark, ETL)

GCP Data Engineer (Java, Spark, ETL)

GCP Data Engineer (Java, Spark, ETL)

Job Description

Position: GCP Data Architect
Location: London – Hybrid (2-3 days onsite)
Employment: Contract
Duration: 6 months with potential extensions
Rate: £500- £600 per day (Inside ir35)
Start Date: ASAP
Language: English

As a GCP Data Architect, you will be responsible for designing, implementing, and optimizing data solutions on Google Cloud Platform (GCP). You will work closely with cross-functional teams, ensuring scalable, efficient, and secure data architectures that meet business needs.

Key Responsibilities:

  1. Develop and maintain data models, ETL/ELT pipelines, and cloud-based storage solutions.
  2. Design and implement scalable data architectures on GCP.
  3. Optimize data processing, storage, and retrieval for performance and cost-efficiency.
  4. Ensure security, governance, and compliance of data solutions.
  5. Collaborate with data engineers, analysts, and business stakeholders to understand and fulfill data needs.
  6. Drive best practices for cloud data management and analytics.
  7. Troubleshoot and resolve data-related issues.


Key Skills and Knowledge:

  1. 8+ years of experience in data architecture, data engineering, or cloud computing.
  2. Expertise in Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Cloud Storage, etc.).
  3. Strong experience with SQL, Python, and data modeling.
  4. Hands-on experience with ETL/ELT pipelines and workflow orchestration tools (e.g., Apache Airflow, Dataform).
  5. Knowledge of data security, governance, and compliance best practices.
  6. Strong problem-solving, analytical, and communication skills.
  7. Excellent communication and interpersonal skills, with the ability to influence cross-functional teams and stakeholders.
  8. Consulting background.
  9. Rights to work in the UK is a must (No Sponsorship available).


Should you be interested in being considered for this position and would like to discuss further, please apply with your latest CV or share your CV directly with me at .

#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.

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.