specialist, Data Analytics

JOB MISSION STATEMENT The Data Analyst plays a key role in advancing Rustan Coffee’s success by transforming curated, analysis-ready data into actionable insights that enable informed, data-driven decisions and elevate business performance. Operating primarily within the gold layer of the data platform, this role designs and maintains reliable reporting solutions, translates business needs into clear analytical outputs, and delivers impactful insights through effective data visualization. In close partnership with cross-functional teams, the Data Analyst supports the adoption of GenBI capabilities, ensures data accuracy, scalability, and governance, and proactively drives continuous improvement. This role models and acts in accordance with the Starbucks Mission and Values, fostering a culture of curiosity, collaboration, and data-driven decision-making. SUMMARY OF KEY RESPONSIBILITIES Responsibilities and essential job functions include but are not limited to the following: 1. Business Needs Identification Engage directly with business stakeholders to identify and evaluate analytics needs and translate them into well-defined reporting requirements. Determine the critical information needs of stakeholders at different levels — operational, tactical, and strategic. Evaluate existing processes and surface opportunities where better data visibility can drive improvement. Recommend appropriate analytical approaches and data sources to address business questions effectively. 2. Gold Layer Development & Data Modeling Design, build, and maintain dimensional models and semantic layer objects (e.g., measures, hierarchies, calculated fields) on top of curated silver-layer data. Collaborate with the data engineering team to communicate data requirements and ensure gold layer outputs meet downstream reporting needs. Apply data quality validation at the analytical layer to ensure accuracy and consistency of reporting datasets. Maintain documentation of data models, metric definitions, and business logic to support data literacy across the organization. 3. Reporting & Data Visualization Design and develop automated, self-service dashboards and reports that are intuitive, accurate, and aligned to business goals. Apply data storytelling principles to present complex analyses in a clear, concise, and persuasive manner for both technical and non-technical audiences. Manage the reporting lifecycle — from requirements gathering and prototype review through to deployment and ongoing maintenance. Champion best practices in dashboard design, including appropriate use of visual encodings, context-setting, and actionable framing. 4. Generative BI (GenBI) Use Cases Identify and develop use cases where GenBI capabilities (e.g., natural language querying, AI-assisted insight generation) can augment existing reporting workflows. Work with stakeholders to define high-value GenBI applications, translating business scenarios into prototype solutions. Evaluate GenBI outputs for accuracy, relevance, and responsible use, and iterate based on feedback. Stay current on emerging GenBI tools and methodologies and recommend adoption where there is clear business value. 5. Insight Communication & Stakeholder Engagement Translate analytical outputs into business language — making recommendations, not just observations. Proactively surface insights that are relevant to current business priorities, rather than waiting to be asked. Facilitate discussions with stakeholders to validate findings, refine metrics definitions, and align on analytical direction. Contribute to data literacy efforts by helping business users understand and independently use self-service reporting tools. QUALIFICATIONS Education Bachelor's degree in Statistics, Mathematics, Computer Science, Information Systems, Economics, or a related field. Experience 3 to 5 years of experience in a data analyst or similar analytics-focused role. Demonstrated experience building and maintaining dashboards and reports for business stakeholders. Experience working with dimensional models or semantic layers (e.g., star schema, fact/dimension tables, BI semantic models). Track record of working independently on analytics projects from scoping through to stakeholder delivery. Prior exposure to GenBI tools or AI-assisted analytics workflows is an advantage. Technical Skills Proficiency in SQL for querying and validating analytical datasets. Hands-on experience with at least one BI/visualization platform (e.g., Power BI, Looker, Tableau, or equivalent). Familiarity with cloud data platforms and lakehoue/warehouse concepts (e.g., Databricks, BigQuery, Snowflake) is a strong advantage. Working knowledge of data modeling concepts, including dimensional modeling and semantic layer design. Python or R experience for exploratory data analysis is a plus but not required. Competencies Strong analytical thinking with the ability to frame ambiguous business questions into structured analyses. Clear written and verbal communication — able to present findings to non-technical stakeholders without jargon. Collaborative and proactive; comfortable engaging with stakeholders across levels and functions. High attention to detail and a strong sense of accountability for data accuracy and output quality. Learning agility — open to adopting new tools, frameworks, and approaches as the analytics landscape evolves. What We Offer A chance to grow your career and develop your expertise in Data Analytics, with opportunities for future advancement. · Perks upon hire: o Full government-mandated benefits o Partner Perks : Enjoy your Employee Bean (take-home coffee beans!) o Exclusive partner discounts o Access to our Partner Support Line for assistance · Perks upon regularization: o Healthcare Coverage : Intellicare and AVEGA, plus eyewear subsidy o Leave Benefits : 30 days paid time off annually, with up to 10 unused days convertible to cash in December o Gratuity Plan : Financial assistance for retirement, disability, or death after one year of service o Extra Partner Perks : 20% discount at Rustan’s and select SSI stores.