Senior Business Intelligence Analyst | Looker

ENI – Elizabeth Norman International
London
1 week ago
Applications closed

Related Jobs

View all jobs

Analytics Manager

Analytics Manager

Analytics Manager

Analytics Manager

AVP Business Intelligence Analyst - Mandarin Speaking

Senior Commercial Finance Analyst

Senior Business Intelligence Analyst | Looker | Advertising/Media

Clientside media and tech brand

Location: London, UK with hybrid working

Exceptional salary + bonus + great benefits

You MUST have right to work in the UK.


Ready to work with one of the largest datasets in the world?


For this role you will need prior experience working with "user level" or "session based" data.


We’re looking for a data-drivenSenior Business Intelligence Analyst to join a fast-growing Analytics & Insights team within the digital media and advertising space. If you have strong SQL skills, love building dashboards, and can translate complex data into meaningful insights, this could be the perfect opportunity for you!


What You’ll Be Doing:

✅ Designing and maintaining dashboards to empower business teams with data-driven insights.

✅ Creating and optimizing SQL queries and data pipelines.

✅ Supporting the integration and modelling of new data sources.

✅ Providing custom analytics support across multiple European regions.

✅ Collaborating with product teams to develop new data solutions.

✅ Translating business needs into clear and actionable insights.

✅ Building strong stakeholder relationships across various departments.


What We’re Looking For:

Strong SQL experience – you should be using it daily.

Hands-on experience in dashboarding and data visualisation.

Knowledge of large relational databases & cloud computing.

Experience working with digital media, advertising, or TV measurement (a plus!)

Ability to communicate complex data in a clear and simple way.

Strong stakeholder management and cross-functional collaboration skills.

A background in Data Analytics, Business Intelligence, Data Science, or a related field.

Bonus if you have experience with Python, Snowflake, DBT or programmatic advertising.


Why Join Us?

Be part of a dynamic pan-European analytics team.

Work with one of the largest datasets globally.

Drive real impact in a fast-growing industry.

Hybrid working – 3 days in the office, 2 days from home.

25 days holiday + your birthday off.

Bonus scheme + pension contributions.

️ Discounts on products & other perks.


If you’re passionate aboutdata, analytics, and media insights, apply today!


#DataAnalytics #SQL #BusinessIntelligence #DigitalMedia #HiringNow

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.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.