Job Description

You will be part of the Data Science & Analytics team, supporting departments across the business by transforming raw data into meaningful insights. You will play a hands-on role in building SQL data models, designing user-friendly dashboards in Power BI, and automating data workflows to ensure timely, accurate, and actionable reporting.



Main responsibilities

Business Intelligence & Analytics

Design clear and intuitive Power BI dashboards for teams across sales, operations, and executive leadership.

Develop reusable data models and DAX measures to enable self-service insights and scalable reporting.

Translate business questions into data-driven visual stories that support better decision-making.

Data Engineering & SQL

Write clean, efficient SQL queries to extract and prepare data from multiple sources.

Optimise stored procedures, views, and data transformations for clarity and performance.

Build and maintain lightweight, reproducible data pipelines using Python and/or Databricks.

Automation & Workflow Optimisation

Develop scripts to automate ETL, reporting refreshes, or data quality checks using Python (pandas, SQLAlchemy, or PySpark).

Use Git for version control and deploy code using basic CI/CD pipelines when needed.

Documentation & Quality Assurance

Document dashboards, datasets, and SQL logic for transparency and maintainability.

Write tests to validate critical SQL queries or Python code and reduce the risk of data errors.

Collaboration

Work closely with senior data scientists, analysts, and business owners to clarify requirements and deliver value quickly.

Proactively identify and raise data quality issues -- and suggest practical solutions rather than short-term fixes.

Minimum requirements

Qualifications & Technical Skills

A Bachelor's Degree in Mathematics, Statistics, Computer Science, Engineering, Biology, or equivalent experience

Strong SQL skills -- including data modelling, query optimisation, and advanced joins/window functions

Power BI expertise -- from semantic model design to interactive dashboard creation (Desktop & Service)

Python proficiency -- especially using pandas for data manipulation and SQL integration

Comfortable with Git (GitHub, GitLab, or Azure Repos) and basic command-line tools

Experience working across Windows and Linux environments

Nice to Have

Familiarity with dbt, Delta Lake, or Databricks

CI/CD workflows for Power BI using tools like Azure DevOps or GitHub Actions

Exposure to high-volume transactional domains such as insurance

Experience with cloud data platforms (e.g., Azure SQL, AWS RDS, or Google BigQuery)

Basic understanding of Docker or containerised deployments