Senior Data Analyst

Accountabilities: You will own the development and continuous improvement of enterprise data models and data workflows, ensuring that teams have access to consistent, well-governed, business-ready information. Your main responsibilities will include: Design, build, and maintain enterprise data models used across multiple business functions, including reliable gold-layer datasets. Develop and manage ETL/ELT pipelines to move, transform, enrich, and validate data across the organization's technology stack. Apply dimensional modeling principles and consistent transformation standards to create scalable, maintainable data structures. Build and maintain interactive, high-performance dashboards and automated reports using Power BI, Tableau, or other business intelligence platforms. Track company-wide KPIs and translate business questions into meaningful metrics, visualizations, and actionable insights. Improve data reliability through testing, documentation, lineage management, and thoughtful data architecture. Support customer activation workflows by delivering accurate attributes, segments, and lifecycle data to downstream platforms. Partner with Marketing, Product, Finance, and Operations to define reporting requirements, metrics, segmentation logic, and customer lifecycle attributes. Collaborate with application engineers, analysts, and machine learning and AI stakeholders to deliver data solutions tailored to their use cases. Contribute to data modeling conventions, code review processes, governance standards, and long-term data strategy. Optimize warehouse performance and manage costs to maintain a stable, predictable, and efficient data environment. Requirements : The ideal candidate combines strong analytics engineering expertise with a clear understanding of data architecture, business needs, and production-level data reliability. You should bring the following experience and capabilities: At least 6 years of professional experience in analytics engineering, including 2 or more years in a senior-level capacity. Proven experience owning production-grade data models that are actively used by other teams. Strong experience working with cloud data warehouses and maintaining predictable performance and costs. Hands-on expertise with relational databases, including schema design, query optimization, indexing, and administration. Deep understanding of dimensional modeling, with the ability to explain and justify architectural and modeling decisions. Practical experience building and maintaining ETL/ELT pipelines and data transformations through version-controlled workflows. Demonstrated ability to improve data quality through testing, documentation, and robust design practices. Familiarity with data governance frameworks, role-based access controls, and personally identifiable information (PII) and data privacy best practices. Experience with identity stitching, consent management logic, or historical data tracking. Background supporting customer analytics, lifecycle analytics, or related business intelligence initiatives. Experience delivering reliable customer attributes and audience segments to downstream tools and platforms. Strong communication and collaboration skills, with the ability to gather requirements and translate business needs into effective data solutions. Experience in franchising, multi-location retail, or consumer services is an advantage, particularly in environments where data spans multiple operational units. A thoughtful, outcome-oriented approach to technology: the focus is on how you solve data challenges rather than the number of tools you have used. Availability to collaborate during U.S. business hours. Legal authorization to work in the United States. Employment sponsorship is not available. Benefits : Compensation commensurate with experience. Health, dental, and vision insurance. Paid time off. Company-paid life and accidental death and dismemberment (AD&D) insurance. Short-term disability coverage. 401(k) plan with company match. Free membership for your dog.