Company
AI & Data Engineering : Data Engineering
CustomerJourneyAnalyticsConsultant
Neural analysis suggests this role is
optimal for Mid candidates.
“Customer Journey Analytics Consultant. Skills: Adobe Analytics, Customer Journey Analytics (CJA), Adobe Experience Platform (AEP), SQL, Databricks, Power BI. Perform UAT verification for new analytics deployments. Investigate and document data quality issues”
What You'll Achieve.
Signing off on launch readiness; Producing clear write-ups of root cause and resolution; Flagging anomalies; Preparing summary materials; Answering time-sensitive questions
Industry & Context.
Investigate and document data quality issues; Tracing discrepancies through multiple data layers; Identifying discrepancies; Answering time-sensitive questions
What They're Looking For.
Must Have
5+ years of experience in web analytics, digital analytics, or marketing analytics, Demonstrated expertise in Adobe Analytics, Working knowledge of Adobe Experience Platform (AEP) concepts, SQL at an intermediate-to-advanced level, Experience with data validation and reconciliation, Experience building dashboards and reports in Power BI, Comfortable working with clickstream / web behavioral data, Experience working in agile environments
Nice to Have
Experience with Customer Journey Analytics (CJA) is strongly preferred, Additional experience with CJA Analysis Workspace or Tableau is a plus, Experience with Braze or other email/push marketing platforms and their analytics integrations, Experience with A testing platforms (e.g., Cro-Metrics, Adobe Target, Optimizely) and statistical test interpretation, Familiarity with affiliate marketing tracking (Impact Radius or similar) and SEO/organic traffic attribution, Experience with international / multi-locale web analytics, Python scripting for data validation or automation tasks
What You'll Do.
Perform UAT verification for new analytics deployments
Investigate and document data quality issues
Contribute to weekly web metrics review
Support ad-hoc analysis requests
Maintain sub-channel and channel definition documentation
How You'll Work.
Team & Collaboration
Prepare summary materials for the analytics lead; Support ad-hoc analysis requests from the MarTech and marketing teams; Communicate progress through Jira
Communication Scope
Producing clear write-ups of root cause and resolution; Communicating progress through Jira
Process & Methodology
Managing tasks across 2-week sprints, Estimating effort in story points
Full Job Description
## Description Consultant ## Primary Skills Adobe Analytics ## Job requirements • Perform UAT verification for new analytics deployments — testing event firing in Adobe Analytics (e.g., e-commerce events, custom events), verifying data collection accuracy, and signing off on launch readiness • Investigate and document data quality issues — tracing discrepancies through multiple data layers (Adobe Analytics → AEP → Databricks → Dashboard) and producing clear write-ups of root cause and resolution Operational Support • Contribute to weekly web metrics review — pulling standard metrics, flagging anomalies, and preparing summary materials for the analytics lead • Support ad-hoc analysis requests from the MarTech and marketing teams — pulling data from Adobe Analytics, CJA, or Databricks to answer time-sensitive questions • Maintain sub-channel and channel definition documentation — updating classification logic as new traffic sources or campaign types are introduced About You • You have 5+ years of experience in web analytics, digital analytics, or marketing analytics • You have demonstrated expertise in Adobe Analytics — including Report Suites, Analysis Workspace, segments, calculated metrics, classification rules, and Processing Rules. This is a core requirement for the role. Experience with Customer Journey Analytics (CJA) is strongly preferred • You have working knowledge of Adobe Experience Platform (AEP) concepts — XDM schemas, datasets, and dataviews. You do not need to be an AEP architect, but you should understand how data flows from collection to reporting • You can write SQL at an intermediate-to-advanced level — including CTEs, window functions, and aggregations — and have experience querying data in Databricks or a similar lakehouse platform • You have experience with data validation and reconciliation — comparing metrics across source systems, identifying discrepancies, and documenting what you find clearly enough for others to act on • You have experienc
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