Technical Data Analyst (SQL)

Clearwater Analytics

Edinburgh, Scotland

22 months ago

Applications closed

Related Jobs

View all jobs

Marketing Data Analyst

Armstrong Lloyd Basingstoke, Hampshire, United Kingdom

£50,000 – £60,000 pa Hybrid

Data Analyst

Travail Employment Group Wellingborough, NN8 1AF, United Kingdom

Business Analyst - Compliance & Data

Randstad Technologies Recruitment London, City And County Of the City Of London, United Kingdom

£60,000 – £65,000 pa Remote

Data Modeller

BrightBox Group United Kingdom

£500 – £600 pd Hybrid

Senior Data analyst

Pontoon Bromley, Greater London, United Kingdom

Senior Data analyst

Pontoon Bromley, London, United Kingdom

Hybrid

Posted: 31 Jul 2024 (22 months ago)

Save job

Create job alert

Applications closed

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

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Apr 9, 2026

Products

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Apr 5, 2026

Jobs

Data Science Jobs UK 2026: What to Expect Over the Next 3 Years

Data science has spent the past decade being described as the sexiest job of the twenty-first century. By 2026, the reality is both more nuanced and more interesting than that label ever suggested. The discipline has matured, fragmented, deepened, and in some respects reinvented itself — and the jobs market has changed with it in ways that create genuine opportunity for those who understand what employers actually want, and genuine difficulty for those still operating on assumptions formed five years ago. The data science jobs market of 2026 is not simply a larger version of what it was three years ago. The generalist data scientist — equally comfortable wrangling data, building models, and presenting insights to the board — is giving way to a more specialised landscape where employers know exactly what problem they are trying to solve and are looking for candidates with the specific depth to solve it. Machine learning engineering, causal inference, experimentation, AI product development, and domain-specific applied science have all emerged as distinct career tracks within what was previously a single, loosely defined profession. At the same time, the arrival of large language models and the broader AI capability wave has both threatened and created data science roles in equal measure. Some of the work that junior data scientists spent their early careers doing — data cleaning, exploratory analysis, basic model building — is being partially automated by AI tooling. But the demand for practitioners who can evaluate AI systems rigorously, apply statistical thinking to complex business problems, and build the data foundations on which AI depends has grown considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what data scientists are expected to build and know, and how to position a data science career that will remain valuable as the field continues to evolve around them. This article breaks down what the UK data science jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.

Mar 24, 2026

Jobs

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.