Data Analyst

Role Overview As a Data Analyst on the Data Science Team, you’ll sit at the heart of our client delivery model — owning the recurring reporting, data quality, and analytical support that our top clients and internal stakeholders depend on. You will work closely with a small, high-capability team and will be the primary point of contact for day-to-day reporting delivery. The right person brings strong SQL and BI tool skills, a high degree of ownership, and the ability to manage their own workload across multiple reporting deadlines.

This is a role for someone who takes pride in accurate, timely, well-structured reporting and who wants to grow in an environment that values both technical depth and business impact. Own end-to-end delivery of recurring and ad hoc reports for both client and internal stakeholders — ensuring accuracy, timeliness, and consistency across all outputs Maintain and improve existing report templates and dashboards in Power BI Own data quality checks and validation as the last line of defence before data reaches the client, including frameworks that catch anomalies, missing values, and inconsistencies at source Document report logic, data sources, refresh schedules, known caveats, and data issue resolution status for all owned reports; contribute to rationalisation of the existing report portfolio Maintain a handover-ready worklog so all reports can be covered during absences Identify opportunities to automate or streamline manual reporting steps and raise them with the team Work within agreed time zone overlap hours for stand-ups, planning, and ad hoc calls with the North American team; communicate proactively about workload, blockers, and timelines Requirements: 3–5 years of experience in a data analyst, BI analyst, or reporting analyst role Strong proficiency in SQL: comfortable writing and reading complex queries across a cloud data warehouse (Snowflake, BigQuery, or similar) Hands-on experience with Power BI including building, maintaining, and troubleshooting dashboards and reports Solid understanding of data quality principles including validation, anomaly detection, and data lineage Experience managing multiple recurring reporting deadlines simultaneously Strong written and verbal communication in English including the ability to explain data clearly to non-technical stakeholders High attention to detail and a low tolerance for errors in client-facing work Exposure to artificial intelligence Python or R for data manipulation and automation of reporting tasks Experience working in a cross-time zone team with North American or European stakeholders