Business Intelligence Engineer II (London Area)

Cpl Life Sciences
London
2 weeks ago
Applications closed

Related Jobs

View all jobs

Business Intelligence Analyst (HR Data)

Business Intelligence Analyst

Business Intelligence Engineer - Locations considered: London, Paris, Madrid, Milan, Munich, Berlin, EU Heavy and Bulky Services

Business Intelligence Developer

Business Intelligence Analyst

Business Intelligence Engineer - Same Day, EU Same Day Speed Innovation

Business Intelligence Engineer II

Hybrid – London

Up to £350 a day

Inside IR35

6 Months

Key Skills:

SQL

Experience in Data or BI space

Experience with a virtualization tools, good understanding of data


Key job responsibilities

The successful candidate will thrive in a data driven environment that it driven to deliver insights that is timely, accurate and actionable to aid decision support. Motivated by solving complex problems and excited about using data analytics to drive a business forward, the successful candidate will relish the opportunity of driving forward Prime Video's analytics to the next level. Some of the key responsibilities of this role will include:

• Own business-critical reporting that is leveraged globally by hundreds of users; from developing and maintaining large-scale data structures and ETL pipelines to creating reporting in Quicksight or Excel.

• Gather business requirements from key stakeholders in Finance and Business teams, and translate into scalable and automated solutions.

• Provide informed analysis, insight and recommendations around our business metrics to drive optimisation and more effective decision making.

• Build strong relationships with the Data Engineering and Core Analytics Tooling teams to enhance upstream data sources and develop data processes to enable more scalable and accurate reporting.


Basic qualifications

Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc.

Experience with data visualization using Tableau, Quicksight, or similar tools

Experience with data modeling, warehousing and building ETL pipelines

Experience in Statistical Analysis packages such as R, SAS and Matlab

Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

Experience with SQL

Experience in the data/BI space

Preferred qualifications

Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift

Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets


If you are interested please apply or send your CV to

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.

Careers Education

Top 10 Best UK Universities for Data Science Degrees (2025 Guide)

Discover ten of the strongest UK universities for Data Science degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right programme for you. Data is the currency of the modern economy, and professionals who can wrangle, model and interpret vast datasets are in demand across every sector—from biotechnology and finance to sport and public policy. UK universities have been at the forefront of statistics, artificial intelligence and large-scale computing for decades, making the country a prime destination for aspiring data scientists. Below, we profile ten institutions whose undergraduate or postgraduate pathways excel in data science. Although league tables vary each year, these universities have a proven record of excellence in teaching, research and industry collaboration.

Jobs Careers

Veterans in Data Science: A Military‑to‑Civilian Pathway into Analytical Careers

Introduction The UK Government’s National AI Strategy projects that data‑driven innovation could add £630 billion to the economy by 2035. Employers across healthcare, defence, and fintech are scrambling for professionals who can turn raw data into actionable insights. In 2024 alone, job‑tracker Adzuna recorded a 42 % year‑on‑year rise in data‑science vacancies, with average advertised salaries surpassing £65k. For veterans, that talent drought is a golden opportunity. Whether you plotted artillery trajectories, decrypted enemy comms, or managed aircraft engine logs, you have already practised the fundamentals of hypothesis‑driven analysis and statistical rigour. This guide explains how to translate your military experience into civilian data‑science language, leverage Ministry of Defence (MoD) transition programmes, and land a rewarding role building predictive models that solve real‑world problems. Quick Win: Take a peek at our live Junior Data Scientist roles to see who’s hiring this week.

Jobs

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.