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Senior Data Analyst, BI & Analytics
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PayRange is a leading fintech and mobile commerce platform transforming the unattended retail industry through innovative payment and technology solutions. Our platform enables consumers to make seamless mobile purchases across vending, laundry, amusement, coffee, and other self-service environments. With a growing global presence across North America, Europe, and Asia, PayRange is helping modernize everyday transactions while powering a connected ecosystem for operators, partners, and consumers. As we continue to scale through growth, innovation, and acquisition, data is becoming increasingly central to how we operate, measure success, and make decisions across the business. About the Role PayRange is looking for a Senior Data Analyst, BI & Analytics to become the company's first dedicated data and business intelligence owner. Reporting to the Founder/CEO, you will work closely with the leadership team to build trusted reporting, dashboards, data sources, and analytical foundations used across the company. This is a hands-on role for someone who is equally comfortable writing SQL, building Tableau dashboards, modeling data, reconciling metrics, and working with business leaders to turn objectives into measurable operating insights. You will support Finance, Sales, Marketing, Operations, Support, Product, and Executive leadership. You will work with data from systems such as Postgres, BigQuery, Salesforce, Zendesk, QuickBooks, NetSuite, Tableau, and other internal and external sources. What you will do Write SQL queries, views, and analytical tables that turn raw data into usable business datasets. Build and maintain trusted dashboards, reports, and published data sources for executives and operating teams. Define and document core business metrics, including revenue, transaction activity, customer/operator health, support trends, sales performance, operational performance, and other KPIs. Partner with Finance on SaaS metrics including ARR walks and retention reporting Work with Sales, Marketing, Operations, Support, Product, and Engineering to understand business questions and translate them into data models, dashboards, and insights. Identify data quality issues, investigate discrepancies, and establish checks to improve trust in company reporting. Help design the analytics layer that enables self-service reporting and consistent metrics across the organization. Prioritize data requests and balance quick-turn analysis with long-term scalable reporting. Train and support business users in how to interpret dashboards and use data effectively. Help shape the future data stack, including tools, governance, documentation, and reporting standards. What we are looking for 6+ years of experience in data analysis, business intelligence, analytics engineering, or a related role. Advanced SQL skills and experience working with relational databases and/or cloud data warehouses. Strong Tableau experience, including dashboard design, published data sources, extracts/live connections, calculated fields, and performance considerations. Experience building reusable data models, reporting tables, views, or semantic layers. Strong business judgment and ability to translate ambiguous questions into clear metrics and analysis. Experience working with cross-functional teams such as Finance, Sales, Marketing, Operations, Support, and Product. Ability to communicate clearly with both technical and non-technical audiences. Strong data quality mindset, including validation, reconciliation, documentation, and root-cause analysis. Self-directed working style and ability to operate as the primary data person in the company. Nice to have Experience with BigQuery, Postgres, dbt, Git, Python, Airflow, AWS, or similar tools. Experience with Salesforce, Zendesk, NetSuite, QuickBooks, or other business systems. Experience in payments, fintech, IoT, marketplace, usage-based, B2B, or recurring-revenue businesses. Experience supporting executive, board, finance, or company operating reviews. Familiarity with data governance, metric definitions, and data cataloging. What success looks like In the first 90 days, you will understand the company's core data sources, build relationships with key stakeholders, take ownership of existing reporting, and deliver improvements to the executive dashboard and core business metrics. Over time, you will establish the company's trusted data foundation, reduce manual reporting, improve confidence in key metrics, and help every department make better decisions with data.
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- English
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