Senior Data Analyst

Tillster • Las Vegas, NV

2d • Hybrid

About The Position

Tillster is hiring a Senior Data Analyst to own complex analytical initiatives and deliver actionable insights to customers, executives, and internal stakeholders. The role partners with Marketing, Product, Finance, Engineering, Account Management, and Support/Operations to frame business questions, conduct analysis, communicate findings, and support decisions. The position is hybrid and requires working Eastern Standard Time in the United States.

The analyst is the team's primary Google Analytics subject matter expert, responsible for GA4 reporting, tracking plans, custom dimensions and metrics, and integration with the data warehouse. The role also develops and maintains Looker dashboards, Explores, and LookML, and supports reliable, canonical metric definitions and self-service analytics.

The role owns data quality and freshness for its data products, uses advanced SQL, and collaborates with Analytics Engineers and Data Engineers on data models, pipelines, and performance. It also partners on customer analytics and presents machine-learning outputs accurately in dashboards and narratives.

The Senior Data Analyst establishes analytical standards, reviews code, mentors Junior Data Analysts, and contributes reusable team assets and governance guidance. The role applies LLM and AI tools in practical analytics workflows and builds self-service analytics agents, including defining validation and quality standards for AI-generated outputs.

Tillster describes itself as a global provider of digital ordering and customer engagement solutions for restaurants. The company emphasizes customer focus, collaboration, innovation, data-informed decisions, results, ownership, and enthusiasm. The position does not offer visa sponsorship.

Requirements

• 5–7 years of total experience in core technical skills.
• 4–5 years of advanced SQL experience, including window functions, CTEs, complex analytical queries, and query optimization.
• 3–4 years of business intelligence tools experience, with expert Looker skills including LookML, Explores, dashboards, visualization, and self-service analytics design.
• 2–3 years of Google Analytics experience, including GA4 implementation, configuration, reporting, tracking strategy, and warehouse integration.
• 2–3 years of experience in experimental design and statistical testing.
• 3–4 years of statistical analysis experience, including descriptive and inferential statistics, trend analysis, and anomaly detection.
• 1–2 years of hands-on AI-augmented analytics experience with LLMs such as GPT-4, Gemini, or Cortex Analyst; AI agent development, prompt engineering, and output validation.
• 4–5 years of stakeholder management experience, including cross-functional collaboration, executive communication, presentations, and trusted-advisor relationships.
• 3–4 years of business analytics experience, including customer analytics, segmentation, LTV, churn, KPI development, metric definition, and translating business questions into analytical frameworks.
• 2–3 years of team leadership experience, including mentoring junior analysts, code review, standards enforcement, and development of team practices and documentation.
• 3–4 years of project management experience, including end-to-end analytical project ownership, managing concurrent initiatives, and proactive insight delivery.

Nice To Haves

• 1–2 years of Python or other programming experience for data manipulation and automation.
• Experience with version control (Git) and code review.

Responsibilities

• Own complex analytical initiatives from business-question framing and scoping through execution, presentation, and stakeholder follow-through; proactively surface KPI trends, anomalies, opportunities, and risks.
• Provide ad-hoc analysis for customers, executives, and internal stakeholders, including interpretive framing and actionable recommendations.
• Advise cross-functional stakeholders, challenge assumptions when the data suggests a different conclusion, and translate findings into decision-relevant narratives.
• Design and support statistically valid A/B tests, including hypotheses, sample sizing, success and guardrail metrics, and analysis of results.
• Own GA4 reporting, custom dimensions and metrics, tracking-plan validation, and GA-to-warehouse integration; advise on tagging for product features and launches.
• Build and maintain Looker Explores and dashboards, and develop documented, tested LookML for owned domains in line with semantic-layer standards.
• Maintain canonical and unambiguous metric definitions; identify and resolve discrepancies between business intent and semantic-layer implementation.
• Expand self-service analytics for non-technical users, targeting coverage across at least two new business units per half-year.
• Maintain the accuracy and consistency of production Explores and dashboards as data-warehouse structures change.
• Own the accuracy and freshness of in-scope data products; investigate quality issues with root-cause evidence and coordinate upstream fixes.
• Write performant SQL and collaborate with Data Engineers on query optimization, compute efficiency, and derived-table design.
• Collaborate with Analytics Engineers on LookML architecture and semantic-layer design, providing analytical requirements and validating business logic in data models.
• Partner on customer analytics definitions for segmentation, LTV, and churn; accurately surface Data Science model outputs in dashboards and analysis.
• Diagnose data freshness and quality issues in pipelines feeding owned dashboards, escalate to appropriate teams, and communicate resolution timelines.
• Establish team coding standards and analytical best practices, including SQL and LookML conventions, documentation, and PR reviews.
• Conduct substantive code reviews and mentor Junior Data Analysts through paired analysis, feedback, and structured reviews; track development and escalate blockers to the Manager.
• Create reusable team assets such as SQL patterns, LookML components, analysis frameworks, and documentation templates.
• Contribute at least one standards update, governance policy, or best-practice guide per year.
• Use LLM and AI tools hands-on to accelerate analytics workflows, including insight narration, anomaly detection and explanation, and dashboard annotation.
• Design and build natural-language self-service analytics agents for non-technical stakeholders, owning prompt design, output validation, and iteration.
• Configure Cortex Analyst or equivalent AI-assisted BI platforms, including semantic-model templates and YAML definitions for accurate, governed responses.
• Define quality standards for AI-generated analysis, including accuracy checks, hallucination detection, and review before sharing outputs externally or with executives.
• Prototype AI tools that reduce repetitive analytical work and present build-versus-buy recommendations and lessons learned to the Manager.

Benefits

• Medical, dental, vision, and flexible spending account (FSA) benefits for eligible full-time regular employees and their dependents.
• Healthcare and Dependent Care reimbursement programs.
• Employee Assistance Program (EAP) and Optum Care 24-hour confidential medical counseling services.
• Ten paid holidays per calendar year.
• Paid time off: 15 days during the first 12 months of continuous service and 22 days in subsequent years for full-time regular employees; eligible part-time employees receive prorated PTO.
• Eligibility to participate in the 401(k) Plan beginning on the employment start date.
• College tuition and education assistance programs.
• Udemy Learning courses and ongoing learning and development opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed