Here at Tarro we build products that empower small brick and mortar restaurants by liberating them of the operational burden of running their business. We accomplish this by providing a frictionless connection between them and their customers through our multi-product ecosystem offering AI-enabled order taking, delivery enablement, payment solutions, and point-of-sale software. At Tarro, we use a combination of bits (technology) and atoms (people) to solve real world problems facing small business owners.
We obsess over placing our customers first and working backwards from there. When our customers succeed, we succeed. The restaurant industry in the US is over a $1 trillion total addressable market (TAM), but remains relatively underserved by technology. Large chains are able to afford expensive tech that gives them a huge advantage; we believe that small restaurant owners deserve access to the same technologies at an affordable price.
Tarro has been profitable for nearly a decade and has seen 5x revenue growth in the last four years. As of our last fundraising round in mid-2022, we were valued at $450M and have since seen substantial growth across customer acquisition, product development, and company headcount. Thousands of loyal restaurants have entrusted Tarro with their success, and together we have supported nearly 20 million customers. We are proud to be named one of Built In’s top companies to work for in 2023.
To learn more about our culture, values and how you can be a part of helping mom & pop restaurants thrive, please visit us here! Helping restaurants thrive, not just survive.
We’re looking for a Data Analyst (Analytics Enablement) to improve how teams across Tarro access and use data day-to-day. This role is the front line for data questions: you’ll own intake and triage for ad-hoc requests, resolve common questions quickly using dashboards/SQL, and convert larger work into tracked tasks with the right owners.
This is a high-impact opportunity to work in a fast-paced, profitable startup where you’ll have real ownership, move quickly, and see your analyses/work directly influence product and business outcomes.
We’re also looking for someone who can excel at enablement and, as they ramp, grow into broader analytics projects and data engineering-adjacent work based on performance and team needs.
Own internal Slack data intake, ensuring first response within one hour during coverage hours.
Partner with the Data Team to identify and implement automation opportunities that reduce recurring asks (documentation, dashboards, LLM-assisted discovery/answers, and lightweight validation checks).
Help stakeholders clarify vague requests by aligning on: decision/question, metric definition, timeframe, filters, and output format.
Resolve low-to-moderate complexity requests using Lightdash (including Ask AI) and basic SQL in Snowflake.
Troubleshoot metric discrepancies (e.g., dashboard A vs dashboard B) by validating definitions, filters, timezones, joins/deduping, and source-of-truth logic.
Build and maintain Lightdash charts/dashboards and lightweight self-serve assets that reduce repeat questions.
Document and maintain datasets, FAQs, and standard processes for reconciliation and validation.
Create and track Jira tasks for complex requests, defining clear requirements, routing to domain owners, and ensuring completion.
Create and review PRs to update labels, metadata, descriptions, or dimensions from upstream fields.
Snowflake (SQL),
AWS (Data storage layer)
Lightdash (dashboards, explores, Ask AI)
dbt + GitHub
Slack + Jira (intake, triage, and task tracking)
3+ years of experience in analytics / BI / operations analytics (or equivalent).
Strong SQL fundamentals (joins, window functions, aggregation, deduping, reconciliation).
Clear written and verbal communication—able to explain metrics and discrepancies to non-technical stakeholders.
Strong ownership and follow-through in high-interrupt environments (many ad-hoc requests, shifting priorities).
Comfortable operating with ambiguity: you ask the right clarifying questions and drive to a clear outcome.
Experience working with BI tools (Lightdash/Looker/Tableau/etc.) and cloud data warehouses (Snowflake preferred).
Comfortable working in a service/SLA-oriented role with high stakeholder volume and rapid turnaround.
Experience supporting business teams directly (Ops/Finance/Support/Product Ops) with fast turnaround.
Interest or experience in LLM-enabled analytics workflows (prompting, evaluation, or improving self-serve discovery).
Familiarity with dbt, data testing (e.g., schema/metric checks), or contributing small improvements to data pipelines with code review.
Experience in restaurants, payments, delivery/logistics, or high-volume consumer products.
This role is onsite in Manila (5 days/week) and will work 2:00am–2:00pm PH time to overlap with US-based stakeholders.
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