National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Technical Data Analyst (SQL)

Clearwater Analytics
Edinburgh
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst (Capital and RWA remediation)

Senior Data Analyst (Capital and RWA remediation)

Senior Data Analyst (Capital and RWA remediation)

Senior Data Analyst (Capital and RWA remediation)...

Business Data Analyst - Migration

Business Data Analyst - Migration

Job Summary:

The Technical Data Analyst is responsible formaintaining investment data for clients. This role involves tasks such as analyzing and organizing raw data, building data systems and pipelines, conducting complex data analysis, and presenting information through data visualization techniques. Additionally, the analyst collaborates with clients and project management teams to grasp customer and company needs. This role requires the ability to merge data from various sources and present it in alignment with customer/company requirements, while also striving to improve data quality and reliability.

Responsibilities:

Utilize your analytical expertise to decipher and organize raw data, transforming it into valuable insights.

Build efficient and robust data systems and pipelines, ensuring seamless data flow.

Dive into complex data sets, conducting thorough analysis and delivering insightful reports on outcomes.

Showcase your findings using cutting-edge data visualization techniques, making data come to life.

Harness the power of multiple data sources, combining raw information into comprehensive and actionable insights.

Continuously explore innovative methods to improve data quality and reliability, contributing to the highest standards.

Develop and implement analytical tools and programs that empower teams to make data-driven decisions.

Collaborate closely with system architects and product development teams, fostering an environment of innovation and excellence.

Required Skills: 

Familiarity with cloud platforms and big data technologies (e.g., AWS, GCP, Azure).

Understanding of database design and data warehouse principles.

Strong understanding of investment data, good to have 

Knowledge of one or more programming languages (e.g. Java, Python, VBA).

Proficiency in data manipulation and data cleansing techniques.

Knowledge of data governance and best practices in data management.

Continuous improvement mindset for self and team.

Ability to work collaboratively in a cross-functional team environment.

Ability to work with large datasets and perform data mining tasks.

Strong computer skills, including proficiency in Microsoft Office.

Excellent attention to detail and strong documentation skills. 

Outstanding verbal and written communication skills.

Strong organisational and interpersonal skills. 

Exceptional problem-solving abilities. 

Education and Experience:

Bachelor’s degree in data analytics, statistics, accounting, computer science, or related discipline.

4+ years of relevant experience in data analytics, reporting, and visualization.

Hands-on experience with SQL and NoSQL databases

Experience with data integration and exchange, transfer, load processes.

Experience with data visualization tools such as Tableau, Power BI, or D3.js.

Familiarity with dbt/Prophecy good to have, but not essential

National AI Awards 2025

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 to Present Data Science Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

The ability to communicate clearly is now just as important as knowing how to build a predictive model or fine-tune a neural network. In fact, many UK data science job interviews are now designed to test your ability to explain your work to non-technical audiences—not just your technical competence. Whether you’re applying for your first data science role or moving into a lead or consultancy position, this guide will show you how to structure your presentation, simplify technical content, design effective visuals, and confidently answer stakeholder questions.

Data Science Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide—refreshed every quarter—so you always know who’s really expanding their data‑science teams. Budgets for predictive analytics, GenAI pilots & real‑time decision engines keep climbing in 2025. The UK’s National AI Strategy, tax relief for R&D & a sharp rise in cloud adoption mean employers need applied scientists, ML engineers, experiment designers, causal‑inference specialists & analytics leaders—right now. Below you’ll find 50 organisations that have advertised UK‑based data‑science vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the kind of employer—& culture—that suits you. For every company you’ll see: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, mission, culture) Search any employer on DataScience‑Jobs.co.uk to view current ads, or set up a free alert so fresh openings land straight in your inbox.

Return-to-Work Pathways: Relaunch Your Data Science Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like stepping into a whole new world—especially in a dynamic field like data science. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s data science sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve gained and provide mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for data science talent in the UK Leverage your organisational, communication and analytical skills in data science roles Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to data science Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to data science Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as a data analyst, machine learning engineer, data visualisation specialist or data science manager, this article will map out the steps and resources you need to reignite your data science career.