Ad Signals Engineer (Adtech / Martech & Analytics)

AdZeta is an end-to-end data‑intelligence & activation platform that helps advertisers acquire high-value customers using the power of predictive LTV modeling.

Location : Remote (North America time zones)

Team : Ad Signals, Data & Activation (pLTV)

Type : Full-time (open to Senior, Staff, or Principal leveling)

The Mission :

The right candidate will own the end-to-end pipeline that converts predictions into bid-ready, calibrated pLTV signals , and reliably activates those signals across Meta (CAPI), Google (OCI / Enhanced Conversions + Value Adjustments) and Amazon (AMC→DSP) . You’ll build resilient GCP pipelines, shape / monitor predictions, and ship server-side conversions that move ROAS, not just dashboards.

Roles & Responsibilities

Feature & modeling interface

Partner with ML to operationalize user-level pLTV features (RFM, product mix, acquisition metadata) with point-in-time joins .

Productionize Vertex AI training & batch / online scoring (Pipelines, Feature Store, Model Registry).

Own calibration (decile calibration tables, winsorization, shrinkage) for stable platform learning.

Server-side activation

Build stateless “ signal translators ” on Cloud Run for Meta CAPI, Google OCI / EC + Conversion Value Adjustments , and Amazon AMC Inputs / Audiences .

Ensure dedupe (event_id parity), rate-limiting , idempotency , and retry / Replay mechanics with DLQs.

Maintain secrets / keys, rotate tokens, and validate payloads (test modes, acceptance checks).

Observability, reliability, and safety

Ship SLOs & alerts : data freshness, EMQ / match rates, adjustment acceptance rates, API error spikes, queue lag, drift.

Operate kill-switches and fallbacks : immediate revenue mode, decile throttling, shadow testing.

Write runbooks for common incidents (schema drift, API 4xx / 5xx, value restatement rejections).

Experimentation & performance

Design A / A and A / Bs (holdouts, geo-lift, incrementality) to validate pLTV value vs baseline.

Iterate on send timing (D0 vs D1–D7), horizon (H=90 / 180 / 365), and value shaping; quantify impact on tROAS / CAC.

What You'll Own (KPIs)

Meta : Event Match Quality (EMQ), dedupe Google : Import latency, Conversion Adjustment acceptance ≥98% , tROAS lift vs. baseline.

Amazon : AMC audience match rate & size (≥2,000 active), DSP performance vs. all-site.

Data / ML : Pipeline freshness SLOs, coverage of hashed IDs, drift / PSI guardrails, on-time retrains.

Reliability :

Core Qualifications :

7-10+ years building production data+ML activation systems (preferably in adtech / martech).

Proficiency with Meta CAPI, Google Ads offline conversions & Enhanced Conversions, Conversion Value Adjustments, hashed identity formatting, and dedupe mechanics.

Expert SQL (BigQuery) and Python (ETL, API clients, data validation).

Hands-on GCP : BigQuery, Pub / Sub, Dataflow, Cloud Run / Functions, Vertex AI (Pipelines, Feature Store, Endpoints).

Strong grasp of identity graphs, point-in-time feature building, and leakage prevention.

Production observability : Cloud Logging / Monitoring, alerting, SLOs; comfort with queues & DLQs.

Security & privacy hygiene : KMS / Secret Manager, VPC-SC, PII handling, RTBF.

Compensation :

Competitive base + performance bonus tied to platform KPIs (acceptance / EMQ / lift). Senior / Staff / Principal leveling available.