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About the Role

LiftIQ is looking for a Senior Analytics Engineer / BI Product Engineer to build the
reporting and analytics products our teams use to run the business.
This is not a traditional BI role where stakeholders provide specifications and you simply
build dashboards. We need someone who can understand the underlying business
problem, determine what users actually need, and turn ambiguous requests into accurate,
actionable analytics.

Often, the best solution will be different from what was originally requested. You should be
comfortable challenging requirements, identifying insights users did not know to ask for,
and designing reports that help people make decisionsnot simply giving them more data.
This is also a highly technical full-stack analytics role that blends analytics engineering
with BI product engineering. You will work across BigQuery, dbt, TypeScript, Next.js, and
React, using Claude Code extensively to accelerate development.

Data correctness is critical. Wrong numbers are worse than crashes.
You will own the accuracy, reliability, and usability of LiftIQ's reporting products
endtoendfrom data modeling and metric definitions to dashboard experience and
permissions.

What You'll Do
Work directly with stakeholders to understand business questions and translate
them into useful analytics products.
Design metrics, reports, dashboards, and visualizations that surface actionable
insights.
Write sophisticated BigQuery SQL and build/extend dbt models,data marts and
dimensional models (facts, dimensions, semantic layers)
Reconcile reporting against source systems and investigate data discrepancies.
Build dashboards end-to-end across the data layer, semantic layer, application
layer, permissions, and automated tests.
Use Claude Code heavily while maintaining ownership of the underlying
architecture, logic, and data correctness.
Protect sensitive financial and compensation data through rigorous server-side
access controls.
Write automated tests for metrics, business rules, and permissions.
Document business logic, metric definitions, and data models to ensure clarity and
consistency across teams
What We're Looking For
Essential
Exceptional SQL skills
Deep experience with analytical SQL, including complex joins, window functions,
attribution, aggregation, data grain, reconciliation, and performance. BigQuery experience
is strongly preferred.
Strong analytical and business judgment
You can understand what decision a stakeholder is trying to make, determine which
metrics matter, and design something more useful than simply fulfilling the original
request.
Strong requirements-gathering skills
You are comfortable working directly with business users, asking the right questions,
understanding unfamiliar processes, and turning ambiguity into a clear solution.
dbt experience
Experience using dbt in a high-scale production data environment. Experience with
dimensional modeling, semantic layers, and metric governance.
Data skepticism
You instinctively validate, reconcile, spot-check, and investigate. You should be
uncomfortable shipping a number you cannot explain.
Testing discipline
Experience building testable analytics logic and automated tests for metrics and business
rules. Experience with version control, PR hygiene, and modular analytics engineering
practices.
English: strong working proficiency (B2+), with the ability to communicate directly with business stakeholders and gather requirements.

Nice to Have
Performance or affiliate marketing experience, including CPL, CPA, EPC, ROAS, and
media-buying economics
Experience with platforms such as Everflow, Ringba, RedTrack, Voluum,
LeadProsper, or HubSpot
GCP / Cloud Run / Cloud Scheduler / Cloud Build
Python ETL and API integrations
Payroll or commission systems experience
Claude API or other LLM application development
Interactive data visualization
Playwright / E2E testing
Tech Stack
Data: BigQuery, dbt, Python ETL, Google Sheets
Application: Next.js 14, TypeScript, React, Tailwind, NextAuth, Neon Postgres
AI: Claude Code, Claude API
Testing: Vitest
Infrastructure: GCP, Cloud Run, Cloud Scheduler, Cloud Build, Docker
What Success Looks Like
A strong person in this role becomes someone the business brings problems, not
dashboard specifications.
If someone says, I need to understand why this buyer's margins dropped," you should be
able to understand the business context, interrogate the data, identify the relevant metrics
and potential causes, and build something that makes the answer clear.

You should be equally comfortable debugging a subtle SQL grain issue, talking with a
stakeholder about how their business works, and using Claude Code to turn the resulting
solution into a production dashboard.

This is a full-stack analytics role, but the hardest part of the job is data correctness,
modeling discipline, and analytical judgmentnot frontend development.
Success also means stakeholders trust your numbers without hesitation, dashboards
become decision tools rather than data dumps, and metric definitions remain consistent
across teams.

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