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Data Analyst

AI Summary
This mid-level Data Analyst role owns end-to-end analysis for assigned business domains and delivers actionable insights to business stakeholders. The position centers on advanced SQL, Looker dashboard development, LookML modeling, data quality investigation, and semantic-layer collaboration. The analyst will support experimentation, GA4 reporting, warehouse integrations, and AI-assisted analytics workflows. Success requires clear stakeholder communication, growing independence, and close collaboration with data engineering and analytics teams.
Remote from
USA
Salary
EUR 70k–85k / yr
Employment
Full Time
Experience
Senior
Published
Apply before
14 Dec 2026
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15
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Opportunity details

About this role.

Data Analyst (Mid-Level)

HYBRID (No Visa Transfers or Sponsorships Available)

Role Summary

The Data Analyst is an individual contributor who has moved beyond supervised execution and is developing the independence, analytical depth, and stakeholder skills needed to progress to Senior level. They own smaller analytical domains end-to-end, contribute meaningfully to team standards, and begin to proactively surface insights rather than waiting to be directed.

What You’ll Do

Analytics & Insight Delivery

  • Deliver analytical work end-to-end for assigned business areas — from scoping and analysis through to presentation and stakeholder follow-through — with minimal re-direction

  • Support ad-hoc analysis for internal stakeholders including Marketing, Product, Finance, and Account Management, providing interpretive framing alongside data outputs rather than data retrieval alone

  • Begin to proactively surface trends, anomalies, and data-driven observations to stakeholders, developing the instinct to flag what matters without being asked

  • Support A/B test experiments under the guidance of the Senior DA — including data preparation, metric tracking, and results summaries — building toward independent experimental design at Senior level

Google Analytics & Data Collection

  • Support the Senior DA in GA4 reporting, tracking plan validation, and custom dimension and metric implementation

  • Develop working knowledge of GA-to-warehouse integration and tagging practices in preparation for owning this domain at Senior level

BI Development & Semantic Layer

  • 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 all 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 DA 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 accuracy and consistency of production Explores and dashboards as underlying data warehouse structures evolve

Data Quality & Platform Collaboration

  • 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 including window functions and CTEs; collaborate with Data Engineers on query optimisation 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

Standards & Collaboration

  • Follow and actively contribute to coding standards, SQL style guides, LookML conventions, documentation requirements, and PR 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 DA

  • Partner closely with Senior Analysts, Data Engineers, and business stakeholders; ask clarifying questions early and communicate proactively on blockers and timelines

AI-Augmented Analytics

  • Apply AI and LLM tools hands-on to accelerate day-to-day analytics workflows — including SQL generation, LookML authoring, documentation, and exploratory analysis

  • Begin experimenting with AI-assisted insight narration and anomaly detection, sharing learnings with the team

  • Develop familiarity with self-serve analytics agent concepts (Cortex Analyst or equivalent) in preparation for owning this capability at Senior level

Continuous Learning

  • 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

About You

Required

  • Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Computer Science, or Engineering — or equivalent practical experience

  • 2–4 years of experience in a data analytics or BI role

  • Strong SQL skills including window functions and CTEs

  • 2+ years of hands-on experience with Looker and LookML development

  • Experience with AWS or Google Cloud data warehouses (Redshift or BigQuery)

  • Demonstrable experience building dashboards and Explores for non-technical business users

  • Working knowledge of software development best practices: Git, PR reviews, 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

Preferred

  • 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 LLM tools applied to analytics workflows

  • Experience with Linux/OSX command line and Git

  • Understanding of ELT pipeline concepts and cloud data infrastructure

  • Prior experience mentoring or supporting more junior colleagues

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.

The Interview Process

  1. Recruiter interview with a Talent Acquisition Specialist

  2. Interview with Data Science Team

  3. Final interview with our Data Science Team Leader

Pay and Benefits (USA)

  • Salary hourly rate is $90,000k – $130,000k 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

No Visa Sponsorship

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.

Apply for this position

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

4/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThe role requires strong hands-on SQL and LookML expertise alongside ownership of production dashboards, data-quality diagnosis, and stakeholder-facing analysis. It also expects the analyst to work with evolving warehouse structures and contribute to team standards with limited direction.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you investigate a discrepancy between a Looker dashboard and a stakeholder's source report?

I would first align on the business definition, reporting period, filters, and grain of both outputs. Then I would validate the LookML logic, joins, derived tables, source freshness, and SQL query results to isolate the point of divergence. I would document the root cause, communicate the impact clearly, and coordinate a fix with analytics or data engineering if the issue is upstream.

Describe how you would build a reusable LookML Explore for non-technical users.

I would begin by understanding the key business questions, agreed metric definitions, and expected reporting dimensions. I would model clear joins, create documented dimensions and measures, add user-friendly labels and descriptions, and ensure the Explore uses performant SQL patterns. Before release, I would validate results with stakeholders and provide example dashboards or guidance for self-service use.

What are window functions and CTEs, and when would you use them?

CTEs improve readability by breaking a complex query into logical intermediate steps. Window functions calculate values across related rows without collapsing detail, such as ranking customers, calculating running totals, or comparing a row with a previous period. I use both to create maintainable analytical queries while preserving the appropriate level of detail.

How would you support an A/B test when working with a senior analyst?

I would help confirm the experiment population, treatment assignment, primary metrics, guardrail metrics, and measurement window. I would prepare clean analysis datasets, monitor data quality during the test, and summarize results with appropriate comparisons and confidence considerations. I would also highlight limitations, such as sample imbalance, tracking issues, or insufficient statistical power.

How do you communicate an analytical finding to a non-technical stakeholder?

I lead with the business implication, explain the most important evidence in plain language, and use a focused visualization where useful. I distinguish facts from assumptions, quantify impact when possible, and provide a clear recommendation or next step. I also invite questions and confirm that the proposed action matches the stakeholder's decision context.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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