Data Solutions Architect

ZipRecruiter
London
2 weeks ago
Applications closed

Related Jobs

View all jobs

Microsoft Data Solution Architect

Senior Data Architect

Lead Data Architect

Principal Data Engineer

Databricks Solutions Architect

Solutions Architect

Job Description

Im looking for a hands-on, highly skilled Data Solutions Architect to join a global Data & AI Consultancy in London. You will split your time between the London office, your home and client site, depending on requirements.

This exciting role is perfect for an experienced Data Engineer whos progressed to an architectural level and is ready to lead the design and delivery of innovative data solutions for a diverse range of clients.

In this role, youll be responsible for guiding technical teams in the development of end-to-end data solutions that address complex business challenges, using both on-premises and cloud-based technologies (Azure, AWS, or GCP). Youll design scalable data architectures, including data lakes, lakehouses, and warehouses, leveraging tools such as Databricks, Snowflake, and Azure Synapse.

The ideal candidate will have a deep technical background in data engineering and a passion for leading the development of best-in-class data solutions. Youll enjoy providing strategic advice to clients, ensuring solutions are tailored to their needs and aligned with future growth.

This is a fantastic opportunity to apply your expertise, stay ahead of emerging technologies, and make a real impact across multiple organisations!

Requirements

  • Excellent scripting skills including SQL and Python
  • Enterprise data modelling experience using tools such as ERwin or Power Designer
  • Experience with data ingestion (both batch and streaming), CI/CD tooling (e.g. Azure DevOps, Terraform etc.) and interrogation with databases such as SQL Server, Oracle, Redshift etc.
  • Experience developing solutions on any major cloud platform: Azure, AWS or GCP
  • Experience with reporting tools such as Power BI, Tableau, Qlik etc.
  • Excellent communication skills with a passion for problem-solving with technology
  • Experience in Financial Services would be beneficial for some major clients, but not essential

Benefits

  • Salary up to £120,000 depending on experience
  • Discretionary bonus up to 12.5%

Please Note: This is a permanent role for UK only. This role does not offer Sponsorship. You must have the right to work in the UK with no restrictions. Some of our roles may be subject to successful background checks including a DBS and Credit Check.

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.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

Data Science Jobs in the Public Sector: Exploring Opportunities Across GDS, NHS, MOD, and More

Data science has emerged as one of the most influential fields in the 21st century, transforming how organisations make decisions, improve services, and solve complex problems. Nowhere is this impact more visible than in the UK public sector. From the Government Digital Service (GDS) to the National Health Service (NHS) and the Ministry of Defence (MOD), government departments and agencies handle vast amounts of data daily to support the well-being and security of citizens. For data enthusiasts looking to make a meaningful contribution, data science jobs in the public sector can offer rewarding roles that blend innovation, large-scale impact, and societal benefit. In this comprehensive guide, we’ll explore why data science is so pivotal to government, the roles you might find, the skills needed, salary expectations, and tips on how to succeed in a public sector data science career.

Contract vs Permanent Data Science Jobs: Which Pays Better in 2025?

Data science sits at the intersection of statistics, machine learning, and domain expertise, driving crucial business decisions in almost every sector. As UK organisations leverage AI for predictive analytics, customer insights, and automation, data scientists have become some of the most in-demand professionals in the tech job market. By 2025, data scientists with expertise in deep learning, natural language processing (NLP), and MLOps are commanding top-tier compensation packages. However, deciding whether to become a day‑rate contractor, a fixed-term contract (FTC) employee, or a permanent member of an organisation can be challenging. Each path offers a unique blend of earning potential, career progression, and work–life balance. This guide will walk you through the UK data science job market in 2025, examine the differences between these three employment models, present sample take‑home pay scenarios, and offer strategic considerations to help you determine the best fit for your career.