At a Glance
- Tasks: Design and implement data solutions for personalised customer experiences while ensuring data quality.
- Company: Join a forward-thinking company in the heart of London with a hybrid work environment.
- Benefits: Enjoy competitive pay, flexible working, and opportunities for professional growth.
- Other info: Collaborative team culture with a focus on innovation and career advancement.
- Why this job: Make an impact by transforming raw data into actionable insights and engaging visualisations.
- Qualifications: Strong SQL skills and experience with dbt, data warehousing, and BI tools required.
The predicted salary is between 36000 - 60000 £ per year.
We are looking for a Data Engineer who will design and implement customer data solutions that enable personalised experiences while ensuring privacy, quality, and accessibility of customer information across all touchpoints.
Length: 12 months
Location: London, UK
Environment: Hybrid - 2-3 days in the office
Key responsibilities:
- Develop and maintain dbt models that transform raw data into trusted datasets for analytics and business intelligence
- Implement data quality tests and monitoring to ensure accuracy and reliability
- Optimise query performance using effective data modelling and materialisation strategies
- Establish and maintain documentation and data dictionaries for analytical models, KPI definitions and metrics frameworks
- Conduct exploratory data analysis to identify trends, patterns, and anomalies in business performance
- Build interactive dashboards and reports that empower self-service analytics
- Design visualizations that clearly communicate complex data stories to both technical and non-technical audiences
What is required to be successful in this role:
- Strong SQL skills with experience in complex data transformations, CTEs and window functions
- Expertise with dbt and modern analytics engineering tools
- Solid understanding of dimensional modelling and data warehousing concepts
- Experience with Git-based workflows for version control and collaboration for analytics
- Knowledge of data testing frameworks and quality assurance practices
- Experience with Snowflake, Databricks, or similar data platforms
- Proficiency in Looker or similar BI tools (Tableau, Power BI)
Data Analytics Engineer employer: Morson Edge (Technology)
Join a forward-thinking company in London that values innovation and collaboration, offering a hybrid work environment that promotes work-life balance. As a Data Analytics Engineer, you'll have access to cutting-edge tools and technologies, alongside opportunities for professional growth and development within a supportive team culture. Enjoy the unique advantage of working in a vibrant city known for its diverse tech community, where your contributions will directly impact personalised customer experiences.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the data analytics space on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your dbt models, dashboards, and any cool projects you've worked on. We want to see your work in action, so make it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for those interviews! Brush up on your SQL skills and be ready to discuss your experience with data quality tests and monitoring. We suggest practising common interview questions related to data engineering to boost your confidence.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for you. By applying directly, you’ll have a better chance of getting noticed by our hiring team, so don’t miss out!
We think you need these skills to ace Data Analytics Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the job description. Highlight your SQL skills, dbt experience, and any relevant projects that showcase your data transformation abilities. 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 explain why you're passionate about data analytics and how your background aligns with our mission at StudySmarter. Keep it engaging and personal – we love a good story!
Showcase Your Projects:If you've worked on any cool data projects, don’t hold back! Include links to your GitHub or any dashboards you've built. This gives us a glimpse into your hands-on experience and creativity in data visualisation.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the best experience possible. Plus, it shows you're keen on joining the StudySmarter family!
How to prepare for a job interview at Morson Edge (Technology)
✨Master Your SQL Skills
Make sure you brush up on your SQL skills before the interview. Be prepared to discuss complex data transformations, CTEs, and window functions. Practising some real-world scenarios can help you articulate your thought process during the interview.
✨Showcase Your dbt Expertise
Since dbt is a key part of the role, be ready to talk about your experience with it. Bring examples of dbt models you've developed and how they transformed raw data into trusted datasets. This will demonstrate your hands-on experience and understanding of modern analytics engineering tools.
✨Understand Data Quality Assurance
Familiarise yourself with data quality tests and monitoring practices. Be prepared to discuss how you've implemented these in past projects to ensure accuracy and reliability. This shows that you value data integrity, which is crucial for the role.
✨Prepare for Visualisation Discussions
Since you'll need to communicate complex data stories, think about how you've designed visualisations in the past. Be ready to share examples of dashboards or reports you've built, especially using Looker or similar BI tools. This will highlight your ability to cater to both technical and non-technical audiences.
