Senior Data Analyst

· Design, build, and maintain high-performing Explores and dashboards in Looker for business stakeholders including Marketing, Product, Finance, Engineering, Account Management, and Support/Operations — owning deliverables end-to-end with minimal re-work.

· Develop LookML for owned domains to a high quality standard — including complex dimensions, measures, derived tables, and Explore configurations.

Ensure all LookML is documented, tested, and consistent with organisation-wide semantic layer standards.

· Ensure metric definitions in owned domains are canonical, unambiguous, and consistent with the definitions governed by the Analytics Engineering team.

Flag and resolve discrepancies between business intent and semantic layer implementation.

· Expand self-service analytics capabilities — enabling non-technical users across Marketing, Customer Success, and Finance to answer their own questions independently, reducing ad-hoc request volume to the team.

Target coverage across ≥2 new business units per half-year.

· Proactively maintain the accuracy and consistency of production Explores and dashboards as underlying data warehouse structures change.

Identify discrepancies before stakeholders encounter them.

· Own the accuracy and freshness of all data products in scope.

Proactively identify and investigate data quality issues — with root-cause evidence — and partner with Analytics Engineers and Data Engineers to resolve upstream problems promptly.

· Write high-quality, performant SQL — including complex window functions and CTEs — and collaborate with Data Engineers on query optimisation, compute cost efficiency, and derived table design for owned analytical workloads.

· Collaborate with Analytics Engineers on LookML architecture and semantic layer design for owned domains — providing analytical requirements that inform model design and validating that data models correctly reflect business logic.

· Partner with the Senior BI & AI Analyst on customer analytics definitions for segmentation, LTV, and churn use cases.

Consume ML model outputs from the Data Science team and surface them accurately in dashboards and analytical narratives.

· Understand the structure of data pipelines feeding owned dashboards sufficiently to diagnose data freshness and quality issues, escalate to the correct team, and communicate resolution timelines to stakeholders.

· Own coding standards and analytical best practices for the team — including SQL style guides, LookML conventions, documentation requirements, and PR review processes.

Conduct structured code reviews that are substantive, consistent, and designed to build capability in Junior Analysts.

· Mentor Junior Data Analysts through paired analysis, direct feedback, and structured review.

Track improvement over time.

Escalate development needs or blockers to the Manager.

· Build and contribute reusable assets to shared team libraries — including SQL query patterns, LookML components, analysis frameworks, and documentation templates — reducing time-to-delivery for the entire team, not just own work.

· Contribute to at least one standards update, governance policy, or best-practice guide per year.

· Apply LLM and AI tools (Gemini, GPT-4, Cortex Analyst, or equivalent) hands-on to accelerate analytics workflows — including automated insight narration, anomaly detection and explanation, and AI-assisted dashboard annotation.

Practical delivered experience required; theoretical familiarity is not sufficient.

· Design and build self-serve analytics agents that enable non-technical stakeholders in Marketing, Customer Success, Finance, and Account Management to query data and surface insights in natural language — without raising tickets or requiring analyst intervention.

Own the full lifecycle from prompt design through output validation and iteration.

· Configure Cortex Analyst or equivalent AI-assisted BI platforms to extend self-service beyond traditional dashboard interaction — including semantic model templates and YAML definitions that produce accurate, governed responses to unstructured business questions.

· Define quality standards for AI-generated analytical outputs — including accuracy validation, hallucination detection, and a review process before AI-generated insights are shared externally or with executives.

· Prototype and propose AI tooling that reduces repetitive analytical work for the team.

Present prototypes to the Manager with a clear build-vs-buy recommendation and documented lessons learned that contribute to the team's shared AI analytics playbook.

Required with Years of Experience

Core Technical Skills (5-7 years total experience)

· Advanced SQL (window functions, CTEs, query optimization)

· Complex analytical queries and performance tuning

· Looker expert (LookML development, Explores, dashboards)

· Data visualization and self-service analytics design

· GA4 implementation, configuration, and reporting

· Tracking strategy and warehouse integration

· Data manipulation and automation

· Version control (Git) and code review

Experimental design and statistical testing

Hypothesis formulation and results interpretation

Descriptive and inferential statistics

Trend analysis and anomaly detection

AI agent development and prompt engineering

AI output validation and quality standards

Executive communication and presentation

Trusted advisor relationships

Customer analytics (segmentation, LTV, churn)

KPI development and metric definition

Translating business questions to analytical frameworks

Mentoring junior analysts

Code review and standards enforcement

Building team best practices and documentation

End-to-end analytical project ownership

Managing multiple concurrent initiatives

Proactive insight delivery

Thriving at Tillster As a member of Tillster, you will embody our core values: · Put Customers First: Prioritize the needs and satisfaction of our customers in all decisions and actions appropriate to Tillster’s stage of development, resources, and stated goals. · Collaborate: Work together effectively, leveraging diverse perspectives to achieve common goals. · Innovate: Embrace creativity and pursue new ideas to drive progress and improvement. · Operate from Data: Use strong critical thinking skills to make informed decisions based on accurate and relevant data. · Drive Results: Focus on achieving tangible outcomes and delivering high performance. · Own It: Take responsibility for your actions and the success of your work. · Be Passionate and Have Fun: Bring enthusiasm to your work and enjoy the journey.

Recruiter interview with a Talent Acquisition Specialist

Final interview with our Data Science Team Leader

hourly rate is $115,000k - $145,000k DOE

Health Benefits: All full-time, regular employees and their dependents are eligible for medical, dental, vision and FSA benefits.

Additional health benefits include Healthcare and Dependent Care reimbursement programs, Employee Assistance Program (“EAP”) and Optum Care 24-hour confidential medical counseling services.

Holidays: The company observes ten (10) paid holidays per calendar year.

Paid Time Off (PTO): Full-time, regular employees earn 15 days of PTO in the first 12-months of continuous service, and 22 days in subsequent years.

Eligible part-time employees earn pro-rated PTO.

Retirement: Effective with your employment start date, you will be eligible to participate in the 401(k) Plan.

Education, Learning & Development: We offer college tuition and education assistance programs; Udemy Learning courses; and ongoing learning and development opportunities.

Making a Difference in the Tillster Way Our business and product mission is to empower restaurants and consumers globally; by empowering, supporting, and nurturing the people who are part of the global Tillster team.

We are committed to fostering an inclusive and diverse work environment where every team member is respected, empowered, and encouraged to grow.

To make this a reality, Tillster is dedicated to embracing diversity in all forms and is proudly an equal opportunity employer.

We do not discriminate based on race, color, religion, national origin, gender identity, sexual orientation, age, family/parental status, marital status, veteran status, disability, or any other protected status.

Follow us on: Tillster: https://www.tillster.com/ Tillster Careers: https://www.tillster.com/careers LinkedIn: https://www.linkedin.com/company/tillster/

Tillster is proudly an Equal Opportunity Employer

Principals only – no Agencies or calls please

Tillster cares about the safety of all our employees—even those we’ve yet to hire

RECRUITMENT FRAUD WARNING We want to help you stay safe during your job search.

Tillster will never:

Request personal/financial information during recruitment

Require payment or fees

Ask for sensitive PII before a formal job offer

Collect information via email or phone (only through secure channels)

Extend offers without in-person or virtual interviews

Red flags: All official communications come from @ tillster.com addresses only Suspicious activity?

Report immediately to Tillster HR, Legal, or Cyber Security teams.

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