Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead data warehouse redesign and optimise data models for performance and scalability.
- Company: Join a forward-thinking company focused on data-driven solutions.
- Benefits: Enjoy 25 days holiday, competitive salary, and private health insurance.
- Why this job: Shape the future of data solutions while growing your skills in a dynamic environment.
- Qualifications: Expertise in SQL, ETL development, and data architecture required.
- Other info: Collaborative culture with opportunities for career development and mentoring.
The predicted salary is between 60000 - 80000 £ per year.
The Senior Data Warehouse Engineer role encompasses full stack BI development skills, from stakeholder requirements gathering, through specification, data mart design, report building and quality management. You will work closely with analytics, data engineering and platform teams to deliver cutting-edge data solutions and help shape the organisation's data-driven future. In your capacity as a Senior Data Warehouse Engineer, you will be a seasoned professional leading many initiatives whilst continuing to learn and grow in the role and further develop your skills alongside acting as an authority within the responsibilities laid out below.
Job Requirements
- Data Warehouse maintenance and schema design - Star, Snowflake, normalisation, de-normalisation
- SQL development
- ETL & ELT development - Talend tools and/or dbt preferable, or equivalent
- Support Report developers - Tableau tools preferable, or equivalent
- End to end BI development (requirements to report delivery)
- AWS technology stack development - S3, Redshift, RDS, Athena, etc
- Big Data platform development - BigQuery
- Working with Insight Analysts/Data Scientists and their environments - e.g. R, Jupyter, Scala
- Some form of non-BI programming experience - e.g. application, website, systems development
- Experience of developing in, or learning, industry useful programming languages - e.g. Java and Python
- Platform familiarity and understanding - Linux and or Unix command line including Bash/Shell scripting
- Experience with version-controlled repositories - Git-based workflows
- Experience with data pipeline orchestration and scheduling
- Nice to have: knowledge of data governance, lineage, and quality monitoring practices.
- Nice to have: software experience of Airflow, Fivetran and Google Big Query
Job Responsibilities
- Lead the architectural redesign of the existing data warehouse to align with modern ELT best practices.
- Responsible for the continued availability of the existing data platform at UNiDAYS for both reporting and Insights; monitoring, response to support tickets, fixes to issues.
- Optimise data models in Amazon Redshift for performance, scalability, and cost efficiency.
- Ensure data quality, lineage, and documentation standards are enforced across pipelines.
- Collaborate with data analysts, engineers, and stakeholders to capture requirements and validate solutions.
- Set up CI/CD practices for dbt deployments and promote version-controlled transformations.
- Support incremental loading strategies and design effective partitioning and snapshotting techniques.
- Assist with production rollout, monitoring setup, and knowledge transfer to internal teams.
- Support to colleagues is essential for this role, including; career development, coaching, and co-development/design.
Competencies
- Data Architecture & engineering: Independently builds scalable pipelines, models data flows, strong understanding of warehouse/lake architecture such as star schema, design and configure of batch/streaming systems to optimise processing.
- Programming & Automation: Expert proficiency in SQL and one of; dbt, python, shell script etc. for pipeline automation, development of ETL, testing/QA/proof of correctness, production release and deployments, optimise data models for performance, scalability, cost efficiency, setup/follow CI/CD practices and implement partitioning and snapshotting techniques.
- Data Quality & Governance: Monitoring, testing and ensuring reliability, compliance, and security of data systems, response to support tickets and fixes to issues, and maintain lineage standards.
- Collaboration & Handoff: Translating business/analyst needs into engineering solutions, clear documentation (data design specification etc.), co-development and co-design, peer reviews, discussions with the team.
- Project & Stakeholder Management: Independently scoping, estimating, prioritising and delivering data projects across teams, representing the team in various cross department contexts and integrate themselves in Agile practices.
- Influence and Leadership: Setting best practices, mentoring, driving platform decisions, cross-team alignment, career development and coaching and propose improvements.
Job Benefits
- 25 days holiday per year increasing with length of service, plus bank holidays
- Competitive salaries
- 4pm finishes every Friday
- Company pension scheme
- Private health insurance (BUPA)
- Dental Insurance (BUPA)
- Income protection policy
- Life assurance policy
- Employee Assistance Program
- Enhanced parental leave pay
- Regular team building activities
- £150 pounds towards your home office set up
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status or disability status.
Senior Data Engineer in London employer: UNiDAYS
Contact Detail:
UNiDAYS Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current employees at the company you're eyeing, especially those in data roles. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best data projects. Whether it's a cool ETL pipeline or a slick dashboard, having tangible examples can really impress during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on SQL and data warehousing concepts. Practice common interview questions and maybe even do some mock interviews with friends to build confidence.
✨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 love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Data Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Engineer role. Highlight your expertise in SQL, ETL/ELT development, and any relevant tools like Talend or dbt. We want to see how you can contribute to our data-driven future!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and how your previous experiences align with our needs. Don’t forget to mention any collaborative projects you've worked on with analytics or data science teams.
Showcase Your Projects: If you've worked on any cool data projects, make sure to include them! Whether it's optimising data models or developing pipelines, we love seeing real examples of your work. This helps us understand your hands-on experience and problem-solving skills.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining the StudySmarter team!
How to prepare for a job interview at UNiDAYS
✨Know Your Data Warehousing Inside Out
Make sure you brush up on your data warehousing concepts, especially around schema design like Star and Snowflake. Be ready to discuss your experience with ETL/ELT processes and how you've optimised data models in the past.
✨Show Off Your SQL Skills
Since SQL development is key for this role, prepare to demonstrate your proficiency. You might be asked to solve a problem on the spot, so practice writing queries that showcase your ability to manipulate and analyse data effectively.
✨Familiarise Yourself with the Tech Stack
Get comfortable with the AWS technology stack mentioned in the job description, particularly Redshift and S3. If you have experience with tools like dbt or Talend, be ready to share specific examples of how you've used them in your projects.
✨Collaboration is Key
This role involves working closely with various teams, so be prepared to discuss how you've collaborated with data analysts and engineers in the past. Highlight any experiences where you translated business needs into technical solutions, as this will show your ability to bridge the gap between stakeholders and engineering.