Data Analyst, Tradable Bits

• You’re a detail-driven data professional with hands-on experience working with ticketing and transactional data at scale
• You enjoy digging into complex datasets, identifying discrepancies across platforms, and building reliable processes that improve data quality and trust
• You’re equally comfortable writing advanced SQL and Python scripts as you are partnering with cross-functional teams to clearly explain findings and drive solutions
• Experience: 3-5+ years working in data analysis for large ticketing or POS implementation with a known platform in the market
• Strong SQL proficiency (complex queries, joins, aggregations, window functions, data validation)
• Expert Data modelling skills
• Python experience for data manipulation, analysis, and automation scripts
• Experience working with 1Tb+ datasets
• Analytical Skills: Strong problem-solving abilities with attention to detail and the ability to investigate complex data discrepancies
• Communication: Excellent written and verbal communication skills with the ability to explain technical findings to non-technical stakeholders
• Organization: Proven ability to manage multiple priorities, meet deadlines, and maintain high standards of accuracy

Desirable

• TradableBits is seeking an experienced data professional to join our Data Operations Team and ensure the quality, accuracy, and reliability of our integrations with ticketing data operations
• You'll be responsible for monitoring and maintaining data from major ticketing platforms, including Ticketmaster, Eventim, Ticketek, and others, ensuring our internal systems and client reporting are accurate and dependable
• Data Quality Management: Perform daily data quality checks across all ticketing platform datasets to identify anomalies, missing records, format inconsistencies, or integration issues
• Reconciliation & Validation: Reconcile data between multiple ticketing sources and internal systems to identify, investigate, and resolve discrepancies
• Reporting Operations: Maintain and update external reporting datasets to ensure accuracy, completeness, and timeliness for stakeholders and clients
• Cross-Functional Support: Serve as the primary point of contact for data quality questions from Sales, Marketing, Finance, and Client Services teams, providing clear analysis and documentation
• Automation & Process Improvement: Lead initiatives to automate data quality checks, validation rules, and monitoring alerts to reduce manual effort and improve data reliability
• Dashboard & Reporting: Build and maintain dashboards in Metabase to track data quality metrics, integration health, and operational KPIs
• Issue Resolution: Troubleshoot data issues and work with technical teams to implement fixes and improvements to data pipelines