• Professional experience in data engineering, BI development, or a closely related data-intensive technical role.
• Prior experience working with HR, workforce, or public sector data is a significant advantage.
• Experience supporting strategy, research, or policy teams with data infrastructure — not only operational or finance reporting — is highly desirable.
Technical Skills — Required
• Advanced proficiency in SQL: complex queries, query optimisation, window functions, stored procedures, and schema design.
• Strong Python skills for data engineering tasks: data wrangling, pipeline scripting, API consumption, and automation (pandas, PySpark, or equivalent).
• Hands-on experience with Power BI (preferred), Tableau, or Qlik — including advanced DAX measures, calculated columns, and report performance optimisation.
• Experience with cloud data platforms: Azure (preferred — Azure Data Factory, Synapse Analytics, Azure SQL), AWS, or GCP.
• Solid grounding in data warehousing concepts: dimensional modelling, star/snowflake schemas, slowly changing dimensions, and partitioning strategies.
• Experience with ETL/ELT orchestration tools such as Azure Data Factory, dbt, Talend, Informatica, or equivalent.