Senior Analytics Engineer

PayJoy, Mexico City, CDMX +1

What you will do

Own PayJoy's Unity Catalog governance model e.g. catalog and schema architecture, tagging and metadata standards, lineage, grants, and PII controls, so that data access is provable to an auditor and self-evident to an analyst rather than tribal knowledge held by a few people
Define and operate the standards that make data trustworthy by default: a tiered certification standard strong enough to carry regulated reporting, service-level objectives on the highest-traffic data products, and strong detection quality on alerts, while retiring the duplicate and abandoned models that dilute trust
Own the governed semantic layer and the transformation development loop (conformed dimensions, canonical entity keys, and single definitions for every cross-functionally consumed measure) so that two teams asking the same question get the same answer, AI-assisted analysis inherits sound semantics, and a new contributor ships a correct model in their first week
Establish how experimentation works at PayJoy, owning the measurement substrate (e.g. experiment metric definitions, exposure tables, guardrail metrics, readout correctness) while advising on tooling selection, statistical approach, and instrumentation architecture with Product Engineering.

What you will do

Own PayJoy's Unity Catalog governance model e.g. catalog and schema architecture, tagging and metadata standards, lineage, grants, and PII controls, so that data access is provable to an auditor and self-evident to an analyst rather than tribal knowledge held by a few people
Define and operate the standards that make data trustworthy by default: a tiered certification standard strong enough to carry regulated reporting, service-level objectives on the highest-traffic data products, and strong detection quality on alerts, while retiring the duplicate and abandoned models that dilute trust
Own the governed semantic layer and the transformation development loop (conformed dimensions, canonical entity keys, and single definitions for every cross-functionally consumed measure) so that two teams asking the same question get the same answer, AI-assisted analysis inherits sound semantics, and a new contributor ships a correct model in their first week
Establish how experimentation works at PayJoy, owning the measurement substrate (e.g. experiment metric definitions, exposure tables, guardrail metrics, readout correctness) while advising on tooling selection, statistical approach, and instrumentation architecture with Product Engineering.