Data Analyst

Role Overview\n\nAs 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.\n\nThe 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.\n\nOwn end-to-end delivery of recurring and ad hoc reports for both client and internal stakeholders — ensuring accuracy, timeliness, and consistency across all outputs\nMaintain and improve existing report templates and dashboards in Power BI\nOwn 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\nDocument 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\nMaintain a handover-ready worklog so all reports can be covered during absences\nIdentify opportunities to automate or streamline manual reporting steps and raise them with the team\nWork 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\n\nRequirements:\n3–5 years of experience in a data analyst, BI analyst, or reporting analyst role\nStrong proficiency in SQL: comfortable writing and reading complex queries across a cloud data warehouse (Snowflake, BigQuery, or similar)\nHands-on experience with Power BI including building, maintaining, and troubleshooting dashboards and reports\nSolid understanding of data quality principles including validation, anomaly detection, and data lineage\nExperience managing multiple recurring reporting deadlines simultaneously\nStrong written and verbal communication in English including the ability to explain data clearly to non-technical stakeholders\nHigh attention to detail and a low tolerance for errors in client-facing work\nExposure to artificial intelligence\nPython or R for data manipulation and automation of reporting tasks\nExperience working in a cross-time zone team with North American or European stakeholders