Senior Data Analyst

We need to output HTML fragment with sections: About the role? Actually the posting includes "About Tillster" then "Are you a passionate data analytics with a knack for data?" then "Job Duties" etc. We need to use

for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must not repeat job title as heading. Must include sections only if posting has real specific content. We have content for About (Tillster description) maybe as "About the role"? Actually "About Tillster" is company description; we could put under "About the role"? The instruction says use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we need to map content accordingly. We have: - About Tillster (company overview) -> could be placed under "About the role" maybe? But "About the role" is about the job, not company. However we have no explicit "About the role" text. Could we skip that heading? We should only include sections when posting has real specific content for it. There's no explicit "About the role" description; we have company description but not role-specific. Might still be okay to put under "About the role" as it's about the role context? The instruction: "use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It's examples, not mandatory to include all. We should include sections only when posting has real specific content. So we need to decide which sections have content. We have: - Responsibilities: The "Job Duties" section with bullet-like paragraphs. That's responsibilities. - Requirements: The "Skills Required With Years Of Experience" section lists required experience and skills. That's qualifications/requirements. - Qualifications: Could be similar to Requirements; maybe we combine? But we could have both Requirements and Qualifications if distinct. The posting lists "Skills Required With Years Of Experience" which includes core technical skills, statistical & analytical skills, AI & emerging technologies, business & communication skills, leadership & mentorship. That's qualifications. - Benefits: The "Pay And Benefits (USA)" section includes salary, health benefits, holidays, PTO, retirement, education etc. So we have Benefits and Pay. - Schedule: The posting mentions "Senior Data Analyst HYBRI- MUST WORK EST( Eastern Standard Time, United States)" indicating schedule requirement: must work EST. That's schedule info. Thus we can include sections: Responsibilities, Requirements (or Qualifications), Benefits, Pay, Schedule. Also maybe "About the role" could be omitted because we don't have explicit role description beyond duties. But we could put company overview under "About the role"? Might be considered filler. Safer to omit About the role if no explicit content. We need to preserve all substantive information, not invent or summarize away detail. Use

• for any list of duties/requirements/benefits. Use

  for prose. We must remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, application instructions. So we need to strip out the "The Interview Process", "Thriving at Tillster" (core values) maybe considered boilerplate? It's not exactly boilerplate but could be considered generic values; but it's substantive? It's about company culture; maybe we keep? The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. Core values might be okay to keep but not required headings. However we have no heading for culture; we could include as a paragraph under maybe "About the role"? But we don't have that heading. Could we add a section "Culture"? Not in allowed headings. Probably better to omit to stay within allowed headings. The instruction says use those headings for section headings; doesn't forbid other headings? It says use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It implies we should use those headings for sections; we could also use other headings but they'd deviate. Safer to stick to those. Thus we will produce:

  Responsibilities

  • ... each duty as li
  We need to break duties into list items. The duties are paragraphs; we can split each major bullet. Let's extract duties: From "Job Duties" section: - Analytics & Insight Delivery: Own the end-to-end delivery of complex analytical initiatives — from framing the business question and scoping the analysis through execution, presentation, and follow-through on stakeholder action. Do not wait to be asked; proactively surface KPI trends, anomalies, opportunities, and risks before stakeholders encounter them. Support ad-hoc analysis for Tillster customers, executives, and internal stakeholders — going beyond data retrieval to provide interpretive framing and actionable recommendations with a clear point of view. Operate as a trusted analytics advisor to Marketing, Product, Finance, Engineering, Account Management, and Support/Operations. Challenge assumptions in business requests where data tells a different story. Translate complex findings into decision-relevant narratives. Design and support A/B test experiments with statistically valid methodology — including hypothesis definition, sample sizing, success and guardrail metric selection, and results analysis. Communicate findings clearly to Product and Marketing stakeholders. - Google Analytics & Data Collection: Act as the team's primary Google Analytics subject matter expert. Own GA4 reporting, custom dimensions and metrics design, tracking plan validation, and GA-to-warehouse integration. Advise on tagging strategy for new product features and platform launches in partnership with the Lead MarTech Solutions Architect. - BI Development & Semantic Layer: 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. - Data Quality & Platform Collaboration: 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. - Standards, Mentorship & Team Development: 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. - AI-Augmented Analytics & Self-Serve Agent Development: 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. We can make each of these as a list item. Now Requirements/Qualifications: The "Skills Required With Years Of Experience" section includes bullet-like subsections. We'll extract each bullet as list item under Requirements (or Qualifications). Since we have both Requirements and Qualifications headings possible, we could put the experience years under Requirements and the skills under Qualifications. But we can also combine into one section "Requirements". The instruction says use headings like Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We could have both Requirements and Qualifications if we split. However the content includes years of experience and skill areas. Could treat "Requirements" as the years of experience and "Qualifications" as the skill areas. But we need to avoid filler. Let's decide: We'll make a section "Requirements" for the years of experience bullet list (Core Technical Skills, Statistical & Analytical Skills, AI & Emerging Technologies, Business & Communication Skills, Leadership & Mentorship). And a section "Qualifications" for maybe the same? That would duplicate. Better to have one section "Requirements" containing all skill requirements. The instruction allows Skills heading as well; we could use Skills heading for the skill list. But we already have Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We could put the skill list under Skills heading, and the years of experience under Requirements heading. However the posting already groups years of experience with each skill area; it's not separate. Simplify: Use "Requirements" heading for the whole skill requirements list (including years). That's acceptable. Now Benefits: The "Pay And Benefits (USA)" section includes salary, health benefits, holidays, PTO, retirement, education etc. We'll split into Benefits (non-salary) and Pay (salary). So Benefits heading will contain health benefits, holidays, PTO, retirement, education etc. Pay heading will contain salary range. Schedule: The line "Senior Data Analyst HYBRI- MUST WORK EST( Eastern Standard Time, United States)" indicates must work EST. We'll put that under Schedule. Now we need to ensure we don't include boilerplate like "The Interview Process", "Thriving at Tillster", "Making a Difference in the Tillster Way", "Follow Us On", "Equal Opportunity Employer", "No Visa Sponsorship", etc. Remove those. Also remove duplicated lines. Now craft HTML. We'll produce:

  Responsibilities

  • Analytics & Insight Delivery: Own the end-to-end delivery of complex analytical initiatives —