Join our dynamic Data Science & Analytics team, where you'll harness the power of SQL, craft insightful Power BI dashboards, and automate workflows with Python. Together, we'll transform raw data into actionable insights that drive smarter decisions across the business. If you're passionate about data and innovation, this is your chance to make an impact!Duties and Responsibilities: Write clean, well‑commented T‑SQL to extract, join and transform data from Analytics& Production database replicas. Optimise views, stored procedures and CTEs for performance and clarity. Maintain simple reproducible data pipelines (Python +pandas or Databricks notebooks) that load curated tables.
Design intuitive Power BI dashboards that surface actionable KPIs for sales, ops and exec teams. Build reusable semantic models (star schema, proper DAX) and publish to Power BI Service with scheduled refreshes. Translate ad‑hoc stakeholder questions into scalable self‑service reports. Script lightweight ETL, data‑quality checks or report refresh jobs (Pandas/SQLAlchemy or PySpark). Version control everything in Git and deploy via simple CI/CD pipelines where appropriate. Document datasets, dashboards and SQL logic for transparency and hand‑over. Write unit / regression tests for critical SQL or Python code.
Work closely with senior data scientists, BI analysts and business owners to clarify requirements and iterate quickly. Proactively flag data‑quality issues and recommend fixes rather than patching symptomsMinimum Qualifications & Technical SkillsBachelor’s degree in Maths, Stats, Computer Science, Engineering, Biology or equivalent experience. SQL: strong query‑writing, optimisation & data‑modelling skills (window functions, indexing). Power BI: adept at dataset design, DAX measures and interactive dashboards (Desktop & Service). Python: comfortable with pandas & basic automation scripts; ability to connect to SQL/Deltalake. Version control with Git (GitHub/GitLab/Azure Repos). Familiar with Windows & Linux CLI basics.
Nice‑to‑HaveExperience with dbt or Delta Lake / Databricks. CI/CD for Power BI (pbi‑tools, Azure DevOps, GitHub Actions). Exposure to insurance or other high‑volume transactional domains. Docker and/or cloud data platforms (Azure SQL, AWS RDS, GCP BigQuery).
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