Business Data Analyst

Job summary

Independently analyze operational, financial, customer, digital, marketing, loyalty, and restaurant data to identify trends, root causes, and actionable business opportunities. Communicate findings through executive-ready visualizations and recommendations, while supporting Databricks Genie configuration, validation, and governed self-service analytics in partnership with cross-functional teams.

Job details

Hi, Job Title: Data Analyst+BA Location: Canada (Remote) JD: Data analyst Perform ad hoc analysis across operational, financial, customer, loyalty, digital, marketing, and restaurant datasets. Independently investigate business questions by exploring data rather than waiting for predefined requirements. Identify trends, anomalies, opportunities, and root causes through deep analytical investigation. Develop hypotheses and validate them using data-driven methodologies. Data Correlation & Insight Generation Correlate data across multiple enterprise systems to uncover relationships that are not immediately apparent. Connect digital customer behavior with restaurant operations, promotions, loyalty, sales, and financial performance. Identify leading indicators and hidden drivers impacting key business metrics. Build meaningful analytical narratives that move beyond reporting into actionable business recommendations. Storytelling with Data Translate complex analytical findings into concise, compelling business stories. Present insights through executive-ready visualizations, dashboards, and presentations. Clearly explain not only what happened, but also: Why it happened What is driving the results Business impact Recommended actions Tailor communication for both technical and non-technical stakeholders. Databricks Genie & Agent Enablement Escalate data quality, modeling, access, or platform issues to the appropriate engineering or platform teams while maintaining ownership of the business question through resolution. Document validated questions, known limitations, business definitions, and usage guidance to improve adoption and trust. Partner with functional teams to determine whether a question should be answered through Genie, direct ad hoc analysis, an existing BI product, or a new reusable analytical capability. Monitor common questions, failed or low-quality responses, and user feedback; troubleshoot issues and recommend improvements to data, semantic definitions, instructions, or model configuration. Test and validate Genie responses against source data and independently written SQL to confirm accuracy, consistency, and business interpretation before broader enablement. Configure and refine Genie instructions, example questions, trusted data assets, metric definitions, business terminology, synonyms, and other contextual guidance needed to improve response quality. Translate recurring ad hoc questions and analytical patterns into candidate Genie use cases, helping move repeatable analysis from manual support to governed self-service. Support the administration and ongoing configuration of Databricks Genie spaces and related Genie Agent capabilities for approved business domains. Cross-Functional Partnership Partner daily with onshore Product, Engineering, Digital, Marketing, Operations, Finance, and Analytics teams. Participate in backlog grooming, planning sessions, analytical workshops, and business reviews. Build strong working relationships while serving as a trusted analytical partner. Proactively clarify ambiguous requirements and recommend analytical approaches. Self-Sufficient Work Management Independently manage multiple concurrent analytical workstreams. Prioritize requests based on business value and urgency. Maintain consistent communication with onshore stakeholders regarding progress, risks, and findings. Identify opportunities for proactive analysis without waiting for assigned work. Demonstrate ownership from problem definition through delivery of business recommendations. Continuous Improvement Recommend improvements to data quality, analytical processes, and reporting methodologies. Identify opportunities for automation and reusable analytical assets. Contribute to the evolution of enterprise analytics best practices. Required Qualifications Bachelor's degree in Computer Science, Information Systems, Statistics, Mathematics, Engineering, Analytics, or related field. 4+ years of experience in Data Analytics, Business Intelligence, or Decision Support. Expert-level SQL skills, including: Complex joins Window functions Common Table Expressions (CTEs) Query optimization Data validation Strong experience analyzing large, complex datasets. Experience with Power BI, Tableau, or similar visualization platforms. Strong understanding of data modeling and relational databases. Excellent written and verbal English communication skills. Demonstrated ability to independently manage competing priorities. Preferred Qualifications Experience using Databricks, Spark SQL, Delta Lake, or Lakehouse architecture. Experience working with cloud data platforms (Azure preferred). Knowledge of Python or PySpark for advanced analytics. Hands-on experience with AI-assisted or conversational analytics platforms (e.g., Databricks Genie/AI/BI, Genie Agents, Microsoft Copilot), including configuration, testing, administration, or enablement. Understanding of semantic layers, governed metrics, business definitions, and metadata used to support trusted self-service analytics. Experience testing conversational analytics outputs and reconciling generated answers to source data or independently developed SQL. Experience with event-based analytics platforms such as Amplitude or Google Analytics. Exposure to customer, digital commerce, or loyalty analytics.

What you’ll do

Independently analyze operational, financial, customer, digital, marketing, loyalty, and restaurant data to identify trends, root causes, and actionable business opportunities. Communicate findings through executive-ready visualizations and recommendations, while supporting Databricks Genie configuration, validation, and governed self-service analytics in partnership with cross-functional teams.

Requirements

Requires a bachelor's degree in a relevant field, at least four years of experience in data analytics, business intelligence, or decision support, and expert-level SQL skills. Candidates should have experience with complex datasets, data modeling, visualization platforms, and clear English communication; Databricks, cloud platforms, Python or PySpark, and conversational analytics experience are preferred.

Listed skills

• Data visualization · Preferred
• Power BI · Preferred
• SQL · Preferred
• Tableau · Preferred
• Data Validation · Preferred
• Data analysis · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• SQL
• Data Analysis
• Business Intelligence
• Data Visualization
• Power BI
• Tableau
• Data Modeling
• Databricks
• Databricks Genie
• Data Validation
• Python
• PySpark
• Stakeholder Communication
• Analytical Storytelling
• Customer Analytics
• Digital Analytics

Job areas

• Data & Analytics
• Technology
• Software
• Consulting

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