- Company Name
- Oscar
- Job Title
- Senior Data Engineer (OLAP)
- Job Description
-
**Job title:** Senior Data Engineer (OLAP)
**Role Summary:**
Lead the design, implementation, and optimisation of OLAP, tabular, and multidimensional data models that power enterprise Power BI dashboards and Excel‑based reporting. Build high‑performance ETL/ELT pipelines, manage analytical infrastructure on AWS, and collaborate closely with BI and business teams to ensure scalable, accurate, and rapid data delivery.
**Expectations:**
• 6‑month contract, outside IR35
• On‑site delivery within a technology‑driven environment
• Demonstrated ability to deliver complex semantic layers that underpin critical reporting
**Key Responsibilities:**
- Architect and maintain SSAS Tabular and Multidimensional cubes, including calculated measures, hierarchies, perspectives, partitions, and aggregation strategies
- Develop and enforce semantic models for Power BI and Excel cube integration, ensuring dynamic loading of data into Excel
- Design, build, and optimise ETL/ELT pipelines using SSIS, dbt, Airflow, or equivalent tools, integrating data from S3 and diverse source systems
- Administer and tune MSSQL Server and PostgreSQL databases for schema design, indexing, performance, and quality
- Manage AWS analytics stack (S3, Glue, Redshift or Athena) to support scalable data warehousing and cube processing
- Evaluate and introduce new modelling techniques and performance optimisations, documenting best practices
- Collaborate with BI, reporting, and business stakeholders to improve data accessibility, model accuracy, and processing speed
**Required Skills:**
- Advanced SSAS Tabular & Multidimensional modelling (MUST)
- Proven design of semantic layers, calculated measures, perspectives, hierarchies, partitions, and aggregation strategies
- Deep knowledge of Power BI semantic modelling (datasets, relationships, optimisation)
- Expertise in DAX, MDX, cube optimisation, and processing strategies
- Strong MSSQL Server experience (schema design, tuning, indexing, profiling)
- Advanced SQL and dimensional data modelling (SCDs, fact/dim, conformed dimensions)
- PostgreSQL optimisation and administration
- Advanced Python programming for data transformation and automation
- Hands‑on ETL/ELT with SSIS, dbt, Airflow, or similar
- Cloud analytics experience: AWS (S3, Glue, Athena/Redshift) and integration with data models
- Understanding of enterprise ETL frameworks, lineage, and data quality
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Information Systems, or a related field (or equivalent practical experience)
---