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- Tasks: Design and optimise OLAP models, build data pipelines, and enhance analytical reporting.
- Company: Join a tech-driven organisation focused on data innovation.
- Benefits: Competitive daily rate, flexible contract, and hands-on experience.
- Why this job: Tackle complex modelling challenges and make a real impact on business analytics.
- Qualifications: Expertise in SSAS, DAX/MDX, and advanced SQL required.
- Other info: Dynamic role with opportunities for professional growth in a collaborative environment.
The predicted salary is between 44000 - 66000 £ per year.
We’re seeking a highly specialised Data Engineer with deep expertise in OLAP, Tabular, and Multidimensional modelling to join a technology-driven organisation on a long-term contract. If you have strong SSAS, semantic modelling, and Excel cube integration experience — this role is for you. This is a hands‑on, onsite position where you’ll architect and optimise analytical models, build high‑performance data pipelines, and design robust semantic layers that directly power business‑critical reporting and Excel‑based analysis.
Required Skills
- Advanced SSAS Tabular & Multidimensional modelling (MUST have)
- Proven experience designing semantic layers, calculated measures, perspectives, hierarchies, partitions, aggregation strategies
- Strong Power BI semantic model understanding (datasets, relationships, optimisation)
- Ability to dynamically load data into Excel using OLAP cubes — essential
- Expert in DAX / MDX, cube optimisation, processing strategies
- Strong expertise with MSSQL Server (schema design, tuning, indexing, profiling)
- Advanced SQL and dimensional data modelling (SCDs, fact/dim, conformed dimensions)
- Experience with PostgreSQL optimisation
- Advanced Python skills
- Hands‑on experience building pipelines using SSIS, dbt, Airflow, or similar
- Strong understanding of enterprise ETL frameworks, lineage, and data quality
- Experience designing and supporting AWS‑based analytical infrastructure
- Skilled in working with S3 and integrating cloud sources into data models
Key Responsibilities
- Design, build, and maintain OLAP, Tabular, and Multidimensional models used across the business
- Develop semantic models and robust data structures for Power BI and Excel cube connectivity
- Create and optimise ETL/ELT pipelines integrating data from S3 and diverse source systems
- Administer and tune MSSQL Server and PostgreSQL for high performance and reliability
- Ensure model scalability, accuracy, consistency, and rapid processing times
- Collaborate closely with BI, reporting, and business teams to improve data accessibility and performance
- Maintain secure, scalable cloud infrastructure in AWS supporting analytical workloads
- Evaluate and introduce new modelling techniques and performance optimisations
If you’re an OLAP/Tabular Specialist who enjoys complex modelling challenges and building powerful analytical layers that the business relies on daily - we want to speak with you. If this sounds like you, apply now for immediate consideration!
Senior Data Engineer (OLAP) employer: Oscar
Contact Detail:
Oscar Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer (OLAP)
✨Tip Number 1
Don’t just sit back and wait for the job to come to you! Slide into the DMs of the job poster on LinkedIn or other platforms. A friendly message can make you stand out and show your enthusiasm for the role.
✨Tip Number 2
Network like a pro! Reach out to current employees at the company or join relevant groups. This can give you insider info and maybe even a referral, which can double your chances of landing that interview.
✨Tip Number 3
Prepare for the interview by brushing up on your OLAP and semantic modelling skills. Be ready to discuss your experience with SSAS and Power BI in detail. We want you to shine and show them why you’re the best fit!
✨Tip Number 4
Apply through our website for a smoother process! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Senior Data Engineer (OLAP)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with OLAP, SSAS, and semantic modelling. We want to see how your skills match the job description, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how your expertise aligns with our needs. Let us know what excites you about this role!
Showcase Your Technical Skills: We’re looking for specific skills like DAX, MDX, and Python. Make sure to mention these in your application and provide examples of how you’ve used them in past projects. We love seeing real-world applications!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Oscar
✨Know Your OLAP Inside Out
Make sure you brush up on your OLAP, Tabular, and Multidimensional modelling skills. Be ready to discuss specific projects where you've designed semantic layers or optimised data pipelines. Having concrete examples will show your expertise and make you stand out.
✨DAX and MDX Mastery
Since the role requires strong DAX and MDX skills, prepare to demonstrate your knowledge. You might be asked to solve a problem on the spot, so practice writing queries and optimising cubes beforehand. This will help you feel confident during the interview.
✨Showcase Your ETL Experience
Be ready to talk about your experience with ETL/ELT pipelines, especially using tools like SSIS, dbt, or Airflow. Discuss how you've integrated data from various sources, including S3, and any challenges you faced. This will highlight your hands-on experience and problem-solving abilities.
✨Collaboration is Key
This role involves working closely with BI and reporting teams, so be prepared to discuss how you've collaborated in the past. Share examples of how you improved data accessibility and performance through teamwork. This shows you're not just a tech whiz but also a great communicator.
