Senior Data Scientist

About the position

• Design, develop and maintain robust data pipelines and ETL/ELT processes using Azure Data Factory, Databricks Pipelines and related services.


• Create and optimise data models and data warehousing solutions to support reporting and analytics needs.


• Build high-quality interactive reports and dashboards; translate business requirements into insightful visualisations.


• Work closely with business stakeholders to gather requirements, define KPIs and deliver actionable analytics.


• Implement and enforce data governance, data quality checks and best practices across datasets and pipelines.


• Develop SQL scripts, stored procedures and Python/PySpark code for data transformation and analysis.


• Collaborate with data engineers, data scientists and platform teams to integrate analytical solutions into the wider data platform.


• Monitor and tune performance of queries, data loads and data storage to ensure cost-efficient operations


• Document data models, pipeline designs, data dictionaries and runbooks for handover and operational support.


• Support data ingestion from diverse sources, including APIs, databases and streaming platforms


• Contribute to automation and CI/CD practices for data solution deployments using Git

Minimum Requirements:

Education

• Bachelor's degree in Computer Science, Data Science, Statistics, Business Analytics or a related field (or equivalent practical experience)


• Minimum of 5+ years’ hands-on experience in data analysis, data engineering or analytics roles with significant Azure exposure


• Demonstrable experience delivering production-ready data solutions, dashboards and documentation in an enterprise environment

 



Knowledge:

• Strong experience with Azure data services (ADF, Azure SQL, ADLS, Azure Data Explorer/Kusto)


• Advanced SQL skills for data extraction, transformation, and analysis


• Proven experience building ETL/ELT pipelines using Azure Data Factory or Databricks


• Expertise in dimensional modelling and data model design (star/snowflake schemas)


• Experience with data visualisation tools (Power BI, Tableau, Celonis) and interactive dashboards


• Solid understanding of data warehousing best practices, including partitioning and indexing


• Strong analytical skills with the ability to translate business requirements into data solutions


• Knowledge of data governance, data quality, and metadata management


• Proficient in Python and PySpark for data engineering tasks


• Strong communication skills to present insights to technical and non-technical stakeholders

Desired Skills:

• Data Scientist
• Python
• SQL
• Azure
• Analytics