Sr. Analytics Engineer(Attribution, BigQuery )

Job highlights

• Ensure dashboard metric definitions are aligned with the attribution model - no dashboard should define revenue or channel differently from the source-of-truth BQ model . Support Power BI reporting for stakeholders who require offline-capable reports . Own the Google Sheets SharePoint migration for reporting infrastructure as part of the ongoing Google sunset initiative

You will be the primary owner of attribution data accuracy, BigQuery analytics layer, and server-side GTM implementation . Day to day, that means maintaining the measurement infrastructure that paid media, eCommerce, and executive reporting all depend on - and being the person who is accountable when numbers don t reconcile.
You ll work closely with the Head of Analytics, the Digital Product team, and paid media channel owners. You ll have a clear mandate: make the attribution data trustworthy, keep it that way, and build the processes so it stays that way when things change - and things always change.

What You ll Own

**1. BigQuery Attribution Pipeline**    

• Own the GA4 BigQuery data model end-to-end: schema, session logic, event definitions, and the revenue attribution layer that reporting draws from

• Define and enforce channel grouping rules in BigQuery - resolving the current discrepancies between GA4 default channel groups and what reports are actually showing

• Maintain the reconciliation process between GA4 session/revenue data and BigQuery exports - establish a documented, repeatable QA cadence so divergences are caught proactively, not reactively

• Write and maintain the SQL transformations that feed Looker Studio dashboards and executive reporting - including eCommerce revenue, session attribution, and conversion rate by channel

• Own the BigQuery dataset structure, access controls, and documentation so that all team members can query with confidence

• Build and maintain attribution accuracy monitoring: automated checks that flag when GA4-to-BQ variance exceeds defined thresholds

  2. Server-Side GTM Ownership

• Take immediate ownership of the three open sGTM migration tickets : container URL update, post-migration tracking validation, and Meta/third-party ad pixel validation via server GTM

• Own the server-side GTM container configuration - tags, clients, triggers, and variable mappings - as the single accountable engineer

• Validate that all paid media vendor pixels (Meta CAPI, Google Ads, Pinterest Tag) are firing correctly through the server container and that conversion data matches platform-reported figures

• Manage consent mode v2 implementation: ensure that cookie-rejected sessions are handled correctly in the server-side pipeline and that their impact on channel attribution is understood and documented

• Define and document the event passthrough architecture: which events fire client-side, which are handled server-side, and why

• Own the ongoing server container QA process - after any significant release or GTM change, run a structured validation before signing off

  3. Attribution Accuracy Ongoing Maintenance

• Maintain and evolve the attribution model as the business adds channels, changes checkout flows, or modifies tracking architecture

• Investigate and resolve the non-consent session impact on direct traffic - currently open (CTE-54704) - and document the expected behavior going forward

• Own the channel grouping logic across all reporting surfaces: GA4 property, BigQuery, and Looker Studio - ensuring consistent definitions everywhere

• Audit attribution data quarterly: identify channels that are over- or under-attributed, document findings, and implement corrections

• Be the internal expert on GA4 attribution settings: attribution windows, cross-channel data-driven attribution, and how they interact with the BigQuery export

• Establish a formal change-management process for attribution - any modification to GTM tags, channel grouping, or BQ schema that affects attribution data must be documented, reviewed, and communicated before it goes live

  4. Reporting Dashboard Support

• Build and maintain the core eCommerce and digital marketing dashboards in Looker Studio that draw from the BigQuery attribution layer you own

• Ensure dashboard metric definitions are aligned with the attribution model - no dashboard should define revenue or channel differently from the source-of-truth BQ model

• Support Power BI reporting for stakeholders who require offline-capable reports

• Own the Google Sheets SharePoint migration for reporting infrastructure as part of the ongoing Google sunset initiative

  5. GTM Web Implementation (Shared Scope)

• Implement and validate GA4 event tracking via GTM for new Digital Product features - PLP filters, PDP interactions, cart events, and checkout flows

• Review and approve data layer specifications from Engineering before implementation begins

• Conduct post-release GTM validation as standard practice - this is non-negotiable before a ticket is closed

Immediate Priorities - First 60 Days

**These are not stretch goals.**  These are the specific open items inherited on day one that have no current owner. The timeline is aggressive because the business risk is real.        **TICKET**         **ITEM**         **WHY IT MATTERS**         **CTE-55223**          Update server GTM container URL web GTM transport URL          Partially migrated container is in an unstable state; must be completed before any further sGTM work         **CTE-55226**          Validate server-side tracking post-migration          No current confirmation that all events are passing through correctly after the migration         **CTE-55227**          Validate Meta third-party ad pixels via server GTM          Paid media attribution depends on this; unvalidated pixels mean untrustworthy ROAS data         **CTE-54706**          GA4 vs BigQuery revenue reconciliation (3rd reopening)          Same root problem opened 3 times - needs a permanent fix and a maintenance process, not another patch         **CTE-54704**          Non-consent session impact on direct traffic classification          Consent mode behavior is misclassifying sessions; affects channel attribution accuracy across all reports    

Skills Experience Required

**SKILL / TOOL**         **WHAT WE NEED**         **LEVEL**         **BigQuery (SQL)**         Write and maintain complex SQL transformations for GA4 export data. Understand the ga\_sessions / events\_ schema, unnesting arrays, sessionization logic, and aggregation patterns used in attribution modeling.         **Expert**         **Server-Side GTM**         Own and operate a live sGTM container. Configure clients, tags, and triggers. Understand transport URL architecture, event passthrough, and how to validate server-side tag firing.         **Expert**         **GA4 Attribution**         Deep understanding of GA4 s attribution model: cross-channel data-driven attribution, attribution windows, conversion credit, and how these interact with the BQ export schema.         **Expert**         **GA4 Property Management**         Custom dimensions, channel groupings, audiences, debug view, and DebugView. Comfortable making configuration changes confidently and validating their impact.         **Proficient**         **Consent Mode v2**         Understand how cookieless pings and modeled conversions work. Know how consent mode behavior affects session attribution and direct traffic inflation.         **Proficient**         **Meta CAPI / Ads Pixels**         Experience validating Meta Conversions API events through a server-side container. Understand deduplication, event match quality, and how CAPI interacts with browser-side pixel.         **Proficient**         **Google Tag Manager (web)**         Implement and debug GA4 tags, triggers, and variables. Write and validate data layer integrations with Engineering. Tag audit and container hygiene.         **Proficient**         **Looker Studio**         Build dashboards that draw from BigQuery via direct connector or Looker Studio data sources. Understand blending, calculated fields, and how to keep dashboards aligned with the BQ data model.         **Proficient**         **Python or dbt (bonus)**         Ability to write Python scripts for data validation or use dbt for BQ transformation management. Not required but accelerates the maintenance workflow significantly.         **Familiar**       
 **Years of experience:**  4-8 years in a digital analytics or analytics engineering role, with at least 2 years of hands-on BigQuery and server-side GTM ownership. Exposure is not sufficient for the Expert-level skills above - we will assess these directly in the interview process.      

 **Preferred Background**    

• Prior experience at a DTC or multi-location retail brand where GA4 and paid media attribution are core business functions
• Experience managing attribution data through a platform migration (UA GA4, client-side server-side GTM)
• Familiarity with Pinterest Conversions API or other retail-relevant ad platform measurement APIs
• Experience with Microsoft Clarity, Power BI, or similar tools used in a Microsoft 365 environment
• Background working within a ticket-driven engineering environment (Jira), collaborating with product and dev teams on data layer specs

Tools Stack

**Measurement Attribution**         GA4, Google BigQuery (GA4 export schema), Server-Side GTM, Consent Mode v2         **Tag Management**         Google Tag Manager (web + server containers)         **Paid Media Measurement**         Meta Conversions API, Google Ads Enhanced Conversions, Pinterest CAPI         **Dashboarding**         Looker Studio, Power BI, Microsoft Clarity         **Project Management**         Jira (CTE + HELPCENTER projects), Confluence         **Collaboration Infra**         Slack, SharePoint, Microsoft 365, Google Workspace (transitioning)         **Nice to Have**         dbt, Python (pandas / pandas-gbq), Git

Skills and Knowledge:

• BigQuery, Server-Side GTM- Google tag manager, GA4 Attribution (Google Analytics 4), Property Management

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