Senior Business Data Analyst

Translate business priorities into scalable data and analytics solutions with a marketing analytics focus.

• Partner with business stakeholders to define problems, desired outcomes, success criteria, and business value.
• Act as a trusted partner for ongoing business requests, focusing on the business need behind each ask.
• Convert business needs into clear, actionable data and analytics requirements.
• Resolve missing or ambiguous requirements and break larger problems into manageable use cases.
• Build domain depth in assigned areas, including processes, metrics, and business logic.
• Lead discovery, solution demonstrations, validation, and obtain business sign off for assigned use cases.
• Collaborate with global stakeholders across North America and Europe, aligned to Eastern Time business operations.
• Extract, combine, analyze, and validate complex datasets using advanced SQL and analytical tools.
• Identify trends, patterns, anomalies, and generate actionable business insights.
• Apply statistical and analytical methods to support business decisions.
• Assess data quality, completeness, and fitness for purpose.
• Translate analytical findings into recommendations stakeholders can act on.
• Use generative AI tools (such as Claude Code or GH Copilot) to accelerate SQL, dbt, and Power BI development, and share learnings with the team.
• Design and develop dashboards, visualizations, and analytical products using Power BI, Qlik, and related tools.
• Create intuitive data experiences that enable stakeholder action on insights.
• Contribute to reusable data products, shared metrics, and standardized analytics solutions.
• Support use cases including customer segmentation, marketing effectiveness, revenue analytics, retention, and predictive analytics.
• Understand source systems, warehouse structures, data relationships, business definitions, and analytical data models.
• Create or adapt analytical data models and transformations for specific use cases.
• Work with Snowflake and tools such as dbt.
• Investigate analytical data issues and collaborate with Data Engineering on production pipelines and shared models.
• Own use cases end-to-end from business problem definition through delivery, validation, and adoption.
• Coordinate contributions from Data Engineering, Data Science, BI, AI, and other specialists as solution lead.
• Manage dependencies, risks, and data availability constraints proactively.
• Reduce dependency on individual experts through office hours, training, self‑service reporting, and recurring metric deep dives.
• Apply established data standards, definitions, governance requirements, and documentation practices.
• Identify data quality risks and coordinate resolution with appropriate owners.
• Maintain awareness of security, privacy, responsible data usage, and enterprise governance requirements.
• Support traceability and consistency of important business metrics and analytical outputs.

• 7+ years of experience in data analytics, business intelligence, analytics engineering, or related field, or equivalent demonstrated experience.
• Advanced SQL skills, including complex joins, common table expressions, window functions, and analytical transformations.
• Strong analytical and data modeling capabilities, including work with relational data, transformations, data quality, validation, and complex datasets.
• Proven ability to partner with business stakeholders to translate business problems into analytical requirements and pragmatic solutions.
• Track record of uncovering insights through data mining and analysis and using business acumen to shape decisions.
• Experience developing dashboards, visualizations, or analytical applications using Power BI, Qlik, or comparable BI platforms.
• Hands‑on experience with Salesforce or other CRM data…