Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and scale data pipelines while delivering insights for global brands.
- Company: Join LatentView Analytics, a leader in data-driven solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make an impact by transforming data into valuable business assets.
- Qualifications: 8+ years in Data Analytics or Engineering with strong SQL skills.
- Other info: Dynamic role at the intersection of data engineering and applied analytics.
The predicted salary is between 48000 - 72000 £ per year.
LatentView Analytics is a leading global analytics and decision sciences provider, delivering solutions that help companies drive digital transformation and use data to gain a competitive advantage. With analytics solutions that provide a 360-degree view of the digital consumer, fuel machine learning capabilities and support artificial intelligence initiatives, LatentView Analytics enables leading global brands to predict new revenue streams, anticipate product trends and popularity, improve customer retention rates, optimize investment decisions, and turn unstructured data into valuable business assets.
Key Responsibilities:
- Building and scaling data pipelines, analytical infrastructure, and dashboard solutions that power customer success insights across multiple international markets.
- Responsible for engineering high-quality data foundations, enabling automated analytics workflows, and implementing new tools and capabilities that enhance data accessibility and reliability across Customer Experience, Digital Experience, and Service Delivery.
- Hands-on, technically focused role at the intersection of data engineering and applied analytics.
Qualifications:
- 8+ years of experience in Data Analytics, Data Engineering, or Applied Data Science.
- Expert proficiency in SQL for complex queries, data modeling, and transformation logic.
- Strong experience with data pipelines and orchestration tools.
- Hands-on experience with big data ecosystems (e.g., Snowflake, Databricks, Spark, AWS/GCP/Azure data services).
- Advanced skills with Tableau, Power BI, or Looker, including data source optimization and dashboard automation.
- Proficiency in Python or R for scripting, data analysis, and automation.
- Familiarity with APIs, RESTful data integration, and Git-based workflows.
- Experience with A/B testing frameworks, statistical analysis, or experimentation design preferred.
- Knowledge of Customer Success or Support Operations KPIs (e.g., resolution rate, contact deflection, AHT) preferred.
- Strong problem-solving, collaboration, and communication skills with both technical and non-technical audiences.
- A proactive, growth-oriented mindset, passionate about improving data accessibility and scalability.
Responsibility: Data Engineering
Senior Data Analyst employer: LatentView Analytics
Contact Detail:
LatentView Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Analyst
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with professionals on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that Senior Data Analyst role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, dashboards, and any cool analytics work you've done. This gives potential employers a taste of what you can bring to the table, and we love seeing creativity in action!
✨Tip Number 3
Prepare for those interviews! Brush up on your SQL queries, data modelling, and be ready to discuss your experience with big data tools. We want to see how you think and solve problems, so practice articulating your thought process clearly.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate candidates who are eager to drive digital transformation with us.
We think you need these skills to ace Senior Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Analyst role. Highlight your expertise in SQL, data pipelines, and any relevant tools like Tableau or Power BI. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data analytics and how your background aligns with our mission at LatentView Analytics. Be genuine and let your personality come through!
Showcase Your Projects: If you've worked on interesting data projects, don’t hold back! Include links or descriptions of your work that demonstrate your skills in building data pipelines or using big data tools. We love seeing real-world applications of your expertise!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at LatentView Analytics
✨Know Your Data Tools Inside Out
Make sure you’re well-versed in the tools mentioned in the job description, like SQL, Tableau, and Python. Prepare to discuss specific projects where you’ve used these tools to solve real-world problems, as this will show your hands-on experience.
✨Showcase Your Problem-Solving Skills
Be ready to tackle some technical questions or case studies during the interview. Think of examples where you’ve faced challenges in data analytics or engineering and how you overcame them. This will highlight your analytical mindset and ability to think on your feet.
✨Understand the Business Impact
LatentView Analytics is all about driving business value through data. Be prepared to discuss how your work has contributed to customer success or improved KPIs in previous roles. This shows that you understand the bigger picture and can align your technical skills with business goals.
✨Communicate Clearly with Non-Technical Audiences
Since you’ll be working with both technical and non-technical teams, practice explaining complex data concepts in simple terms. This will demonstrate your communication skills and ability to collaborate effectively across different departments.
