Data Analyst

Role overview A B2B SaaS organisation is hiring a Data Analyst to turn business and product data into clear, actionable insights that inform decision-making across teams. The role spans querying, reporting, dashboarding, and ad-hoc investigation, with a focus on metrics definition and communicating findings to diverse stakeholders. It is a remote-first position suited to someone who enjoys blending analytical rigour with practical business storytelling.

Responsibilities - Gather and analyse data from multiple internal and external sources. - Write SQL queries and validate the accuracy of results before sharing insights. - Build dashboards and recurring reports using a modern BI platform. - Define and document business metrics so teams share a common view of performance. - Investigate trends, anomalies, and shifts in business or product performance. - Translate analysis into practical recommendations for product, operations, and leadership teams. - Improve data quality and reporting processes, supporting experiments, forecasting, and operational planning as needed.

Requirements - Two or more years of experience in data analysis, business intelligence, or a closely related field. - Strong SQL and spreadsheet skills with a sharp eye for data accuracy and detail. - Hands-on experience with Tableau, Power BI, Looker, or a comparable BI tool. - Understanding of descriptive statistics and data visualisation principles. - Ability to communicate complex findings clearly to both technical and non-technical audiences.

Nice to have - Experience with Python or R for analysis or automation. - Familiarity with data warehouses and analytics engineering workflows. - Knowledge of experimentation, product analytics, or forecasting techniques. - Background working in technology or consumer-facing platforms.

Benefits and work setup - Remote-first work environment with a salary range of $70,000–$95,000 USD annually, depending on experience. - Collaborative culture focused on turning data into practical business outcomes and opportunities to work across business and product data. - Hiring process: application review, recruiter screen, technical/SQL exercise, final stakeholder interview, and offer. - Equal-opportunity employer committed to a diverse and inclusive workforce.