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- Tasks: Build data pipelines and dashboards to drive business insights.
- Company: Join a leading media and tech brand in London.
- Benefits: Enjoy hybrid working, 25 days holiday, bonuses, and discounts.
- Why this job: Work with massive datasets and make a real impact in analytics.
- Qualifications: Strong SQL skills and experience with data pipelines and BI tools required.
- Other info: Open to all applicants, with support for those needing adjustments.
The predicted salary is between 48000 - 84000 £ per year.
Location: London, UK with hybrid working. 3 days in office, 2 days WFH.
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? Love solving big problems with even bigger data? Passionate about building the pipelines and dashboards that power business decisions?
We’re on the hunt for a Business Intelligence Engineer to join a digital-first media team that works with the largest TV dataset in the world. This role is a blend of data engineering and BI expertise—you’ll be building smart, scalable data systems that support insights at scale.
What you’ll be doing:- Build and manage automated data pipelines to power business reporting.
- Design and maintain clean, scalable data models.
- Develop intuitive dashboards and BI tools to help teams self-serve insights.
- Own ETL/ELT processes—think orchestration, monitoring, and performance tuning.
- Collaborate with analytics, marketing, and product teams to deliver impactful insights.
- Support integration of new data sources and optimize existing systems.
- Translate complex business needs into technical solutions using SQL and cloud tools.
- Strong SQL skills.
- Proven experience building and maintaining data pipelines (Airflow, DBT, etc.).
- Familiarity with cloud data platforms like Snowflake, BigQuery, or Redshift.
- Solid experience with BI tools like Looker, Tableau, or similar.
- Understanding of data warehousing and data architecture best practices.
- Ability to simplify complex analytics for non-technical stakeholders.
- Comfortable working with large-scale datasets and performance optimisation.
- Bonus points for Python, GitHub, or experience in media/advertising analytics.
- 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 a data engineer at heart with a BI brain—and want to make a real impact with the insights you power apply now.
ENI welcome applications from all sections of society. Additionally, to ensure people with a disability, impairment, mental or physical health conditions can access and progress in employment. Please let us know if there are any adjustments needed in order to make your interview/screening process as seamless and comfortable as possible.
Senior Business Intelligence Engineer (Looker) employer: ENI – Elizabeth Norman International
Contact Detail:
ENI – Elizabeth Norman International Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Business Intelligence Engineer (Looker)
✨Tip Number 1
Familiarise yourself with Looker and other BI tools mentioned in the job description. Consider building a small project or dashboard using Looker to showcase your skills and understanding of the platform during interviews.
✨Tip Number 2
Brush up on your SQL skills, as they are crucial for this role. Practice writing complex queries and optimising them for performance, as you may be asked to demonstrate your proficiency in SQL during technical interviews.
✨Tip Number 3
Network with professionals in the data engineering and business intelligence fields. Attend relevant meetups or webinars to connect with others who work with large datasets, which could provide insights and potential referrals for your application.
✨Tip Number 4
Prepare to discuss your experience with data pipelines and cloud platforms like Snowflake or BigQuery. Be ready to share specific examples of how you've built or optimised data systems in previous roles, as this will demonstrate your hands-on expertise.
We think you need these skills to ace Senior Business Intelligence Engineer (Looker)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your strong SQL skills and experience with data pipelines. Emphasise any familiarity with cloud data platforms like Snowflake or BigQuery, as well as your proficiency in BI tools such as Looker.
Craft a Compelling Cover Letter: In your cover letter, express your passion for working with large datasets and solving complex problems. Mention specific projects where you've built automated data pipelines or developed dashboards that drove business insights.
Showcase Relevant Experience: When detailing your work history, focus on your experience with ETL/ELT processes and collaboration with cross-functional teams. Highlight any achievements that demonstrate your ability to simplify complex analytics for non-technical stakeholders.
Proofread and Edit: Before submitting your application, carefully proofread your documents for any spelling or grammatical errors. Ensure that your application is clear, concise, and free of jargon, making it easy for the hiring team to understand your qualifications.
How to prepare for a job interview at ENI – Elizabeth Norman International
✨Showcase Your SQL Skills
Since strong SQL skills are a must for this role, be prepared to discuss your experience with SQL in detail. Bring examples of complex queries you've written and how they contributed to business insights.
✨Demonstrate Your Data Pipeline Experience
Highlight your experience with building and maintaining data pipelines, especially using tools like Airflow or DBT. Be ready to explain the challenges you faced and how you overcame them.
✨Familiarise Yourself with BI Tools
As Looker is a key tool for this position, ensure you understand its functionalities. Prepare to discuss any dashboards or reports you've created and how they helped stakeholders make informed decisions.
✨Prepare for Technical Questions
Expect technical questions related to data warehousing and architecture best practices. Brush up on these concepts and think about how you can simplify complex analytics for non-technical stakeholders.
