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Tillster

Digital ordering platforms for restaurants

Data Analyst

Business IntelligenceConfirmed live in the last 24 hours
Full-timeLos Angeles, CA, USA$90k - $130k /yrHybrid

About the Job

Requirements

  • A bachelor's degree in a quantitative field such as Mathematics, Statistics, Computer Science, or Engineering, or equivalent practical experience.
  • Two to four years of experience in a data analytics or business intelligence role.
  • Strong SQL skills, including window functions and common table expressions.
  • At least two years of hands-on experience with Looker and LookML development.
  • Experience with AWS or Google Cloud data warehouses, such as Redshift or BigQuery.
  • Demonstrable experience building dashboards and Explores for non-technical business users.
  • Working knowledge of software development best practices, including Git, pull request reviews, and code style guides.
  • Working knowledge of agile development processes.
  • Ability to translate business questions into analytical tasks with growing independence.
  • Clear, confident written and verbal communication with business stakeholders.

Responsibilities

  • Deliver analytical work end-to-end for assigned business areas, from scoping and analysis through presentation and stakeholder follow-through, with minimal re-direction.
  • Support ad-hoc analysis for internal stakeholders in Marketing, Product, Finance, and Account Management, providing interpretive framing alongside data outputs rather than data retrieval alone.
  • Proactively surface trends, anomalies, and data-driven observations to stakeholders, developing the ability to flag relevant findings without being asked.
  • Support A/B test experiments under the guidance of the Senior Data Analyst, including data preparation, metric tracking, and results summaries, building toward independent experimental design at Senior level.
  • Support the Senior Data Analyst in GA4 reporting, tracking plan validation, and custom dimension and metric implementation.
  • Develop working knowledge of Google Analytics-to-warehouse integration and tagging practices in preparation for owning this domain at Senior level.
  • Design, build, and maintain Looker dashboards and Explores for assigned business areas, owning deliverables with limited rework.
  • Develop LookML, including dimensions, measures, derived tables, and Explore configurations, ensuring work is documented and consistent with team standards.
  • Contribute to the shared semantic layer by flagging metric definition inconsistencies and proposing resolutions in collaboration with the Senior Data Analyst and Analytics Engineering team.
  • Expand self-service analytics for non-technical stakeholders, enabling them to answer their own questions and reducing ad-hoc request volume to the team.
  • Maintain the accuracy and consistency of production Explores and dashboards as underlying data warehouse structures evolve.
  • Take ownership of data accuracy for assigned dashboards and analytical outputs, proactively investigating discrepancies and escalating upstream issues to Data Engineering with clear root-cause evidence.
  • Write performant SQL using window functions and common table expressions; collaborate with Data Engineers on query optimization and derived table design.
  • Develop a working understanding of data pipelines feeding owned dashboards sufficient to diagnose freshness and quality issues and communicate resolution timelines to stakeholders.
  • Begin collaborating with Analytics Engineers on LookML architecture and semantic layer requirements for owned areas.
  • Follow and actively contribute to coding standards, SQL style guides, LookML conventions, documentation requirements, and pull request review processes.
  • Participate in code reviews, providing constructive and consistent feedback that builds quality across the team.
  • Support Junior Analysts through paired working and direct feedback, under the guidance of the Senior Data Analyst.
  • Partner closely with Senior Analysts, Data Engineers, and business stakeholders; ask clarifying questions early and communicate proactively on blockers and timelines.
  • Apply AI and large language model tools hands-on to accelerate day-to-day analytics workflows, including SQL generation, LookML authoring, documentation, and exploratory analysis.
  • Experiment with AI-assisted insight narration and anomaly detection, sharing learnings with the team.
  • Develop familiarity with self-service analytics agent concepts, such as Cortex Analyst or equivalent, in preparation for owning this capability at Senior level.
  • Actively develop skills across advanced SQL, Python, statistical analysis, and cloud data platforms.
  • Build toward independent ownership of experimentation, GA4, and stakeholder advisory at Senior level.

Desired Qualifications

  • Exposure to A/B testing concepts and basic experimental design.
  • Foundational Python skills for data manipulation or automation.
  • Familiarity with GA4 reporting and tracking fundamentals.
  • Experience with AI or large language model tools applied to analytics workflows.
  • Experience with Linux or macOS command line and Git.
  • Understanding of ELT pipeline concepts and cloud data infrastructure.
  • Prior experience mentoring or supporting more junior colleagues.

About the Company

Tillster

Digital ordering platforms for restaurants

Tillster provides digital ordering and engagement tools for restaurants, including online and mobile ordering, delivery management, in-store kiosks, and personalized marketing. It operates as a software-as-a-service platform that charges restaurants subscription fees, transaction fees for orders, and premium analytics and marketing features. The platform connects mobile, web, and in-store channels and uses data analytics to predict customer behavior, optimize conversions, and tailor offers like digital coupons and loyalty rewards. Its global, multi-channel suite combines ordering, delivery management, marketing, and analytics in one system, helping restaurants run operations smoothly and increase repeat business and customer satisfaction.

Company size
201-500
Company stage
Early VC
Total funding
$33.8M
Headquarters
Los Angeles, CA
Founded
2002

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