Own conversion signal delivery end to end: S2S postbacks per channel, event mapping, deduplication across event sources, and match-quality diagnostics

Own identity and match quality: hashed first-party data used for matching, click-ID capture and persistence from landing page to CRM to payment

Own what we optimize toward: value-based bidding, conversion value modelling, event taxonomy and attribution windows

Work across channel specifics: Google Ads conversion diagnostics, Enhanced Conversions, offline conversion import, gclid/gbraid/wbraid and Consent Mode; Meta Conversions API, EMQ and deduplication; TikTok/Snapchat Events API and ttclid/sccid; AppLovin AXON Conversion API; Mintegral tracking URLs, UTM capture and S2S postbacks; affiliate postback integrations, click and sub-ID passing, conversion validation

Build monitoring and alerts for signal errors, latency, coverage, match rates and platform-vs-internal discrepancies

Investigate signal-related performance drops and assess the measurement impact of site releases and ad-platform changes before they hit spend

Own UTM taxonomy and campaign naming conventions across all channels, with automated validation

Own affiliate measurement: deduplication between partner postbacks and paid channels, attribution windows and overlap rules, conversion validation and payout accuracy, partner-level quality and fraud controls

Analyze campaign and partner performance and traffic quality by channel, campaign, creative, geo and placement, including landing-page and checkout funnel conversion, lead quality, repeat purchase, LTV and payback

Find growth points in CAC, ROAS and payback and turn them into recommendations the UA and affiliate teams can act on

Test optimization hypotheses with UA: bidding strategy, which conversion to optimize for, conversion value definitions, audience and creative structures

Build automated Tableau dashboards and ad-hoc reports on conversion values, bidding performance, signal delivery, partner payouts and funnel metrics

Build and maintain custom marketing datasets in BigQuery on top of network, GA4, affiliate and CRM data

3+ years of experience in marketing or product analytics, with hands-on ownership of paid acquisition data

Confident SQL in BigQuery

Solid understanding of statistics: funnel conversion, sample size, telling a real difference from noise

Python (Pandas) for analysis and automation: data validation, conversion uploads, recurring pipelines

Hands-on Tableau, from data model to dashboards the team uses daily

Practical experience with server-side conversion delivery on at least one platform: Meta CAPI, Google offline / Enhanced Conversions, TikTok or Snapchat Events API, or affiliate postback integrations

Understanding of web attribution and performance marketing: click IDs and UTM, attribution windows, why platform, GA4 and internal numbers disagree and which to trust for which decision

Understanding of consent, first-party identity and cookie limitations, and what they do to measured conversions

Experience collaborating with User Acquisition teams and supporting data-driven decisions

Strong analytical thinking and attention to detail

Ability to identify root causes of changes, not just describe the numbers

Ability to build and defend clear business conclusions and recommendations

Proactive mindset and strong communication skills

Experience with A/B testing

Experience using AI tools such as Claude in your analytical work

Experience with affiliate / performance-partner measurement: S2S postbacks, sub-ID structures, conversion validation