Ads Signal 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: 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). Youll 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 D1D7), horizon (H=90/180/365), and value shaping; quantify impact on tROAS/CAC.

What Youll Own (KPIs)

• Meta

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  : Event Match Quality (EMQ), dedupe <2%, CAPI acceptance ?99%.
• 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: <0.1% lost events, <15 min median replay SLA, pager rate trending down.

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.