Data Analyst

Role Summary

We are seeking an Experienced Analyst with strong capabilities across marketing analytics, data engineering, and business intelligence. This role will own end-to-end measurement and reporting for web and app acquisition, including GA4, GTM, and Adjust, with deep analytics and modeling in BigQuery. You will build reliable datasets, attribution-ready reporting, and interactive dashboards that enable stakeholders to understand campaign performance, ROI, funnel health, and growth levers and then act on them.

Responsibilities

1) Measurement Strategy & Tracking (Web + App)

• Own the measurement framework for web and app performance, ensuring accurate tracking across GA4, GTM, and Adjust.
• Design and maintain event taxonomies (web + app), conversion definitions, and KPI hierarchies aligned to business objectives.
• Implement and validate GTM tags, triggers, and variables; ensure consistent UTM governance and channel attribution hygiene.
• Partner with product, dev, and marketing teams to define data layer requirements and maintain tracking documentation (events, parameters, schemas).
• Run ongoing QA, auditing, and anomaly detection to ensure tracking accuracy and consistency across releases.

2) BigQuery Analytics & Data Engineering

• Build and maintain data pipelines and transformations into BigQuery (e.g., GA4 export, adjust exports, ad platform extracts as applicable).
• Develop scalable, well-documented data models for funnel analysis, cohorting, LTV/ROI reporting, and attribution-ready datasets.
• Write performant SQL for analysis and reporting; optimize queries, partitioning, clustering, and cost controls.
• Create unified marketing datasets across sources to enable cross-channel reporting and consistent metric definitions.

3) Dashboards, Reporting & Business Intelligence

• Build interactive dashboards and reporting layers (Looker Studio / Looker / Power BI or equivalent) for stakeholders across marketing, product, and leadership.
• Define reporting standards: metric definitions, refresh cadences, alert thresholds, and selfserve exploration.
• Automate recurring reporting, ensuring stakeholders have timely access to performance trends and insights.
• Develop executive-level views that connect spend to outcomes (pipeline, revenue, retention) and support decision-making.

4) Attribution, ROI & Performance Analysis

• Own campaign performance measurement across channels: acquisition, conversion rate, CAC/CPA, ROAS/ROI, payback period (where applicable).
• Build attribution analysis frameworks (platform attribution + blended measurement) and quantify channel incrementality where possible.
• Conduct deep-dive analyses on funnel drop-offs, cohort performance, geo/audience splits, creative/campaign effectiveness, and budget efficiency.
• Translate analyses into clear recommendations and partner with marketing teams to define tests and optimization actions.

5) Statistical & Advanced Analytics (as needed)

• Apply statistical methods to validate hypotheses, evaluate experiments, and interpret performance changes.
• Build forecasting or scenario models for spend vs. outcomes (e.g., lead volume, CAC, conversion rate sensitivity).
• Establish data confidence practices: baseline comparisons, seasonality controls, and robust benchmarking.

Qualifications

• 4+ years in marketing analytics, BI, data engineering, or a closely related field.
• Strong hands-on experience with BigQuery (advanced SQL; optimization best practices).
• Proven expertise in GA4, GTM, and Adjust for web + app measurement and attribution.
• Demonstrated ability to build interactive dashboards, reporting solutions, and reusable data models.
• Strong understanding of digital marketing KPIs and measurement frameworks (UTMs, conversions, funnels, attribution concepts).
• Solid analytical and statistical foundation: segmentation, cohosting, hypothesis testing, and trend analysis.
• Excellent communication skills: ability to translate complex datasets into decisions and clear narratives.

Preferred Qualifications (Nice to Have)

• Experience integrating ad platform data (Google Ads, Meta, TikTok, Snapchat, LinkedIn) into a unified reporting layer.
• Experience with dbt, Airflow, Cloud Functions, or other orchestration/ELT tooling.
• Familiarity with consent mode / CMP impacts and privacy-safe measurement approaches.
• A/B testing experience (design, analysis, interpretation) and experimentation frameworks.
• Exposure to CRM and revenue attribution (e.g., HubSpot, Salesforce) and lead lifecycle analytics.

Tools & Technical Stack (Typical)

BigQuery, GA4 Export, Adjust raw data exports

Google Tag Manager, GA4 configuration, event parameter standards

BI tools: Looker Studio / Looker / Power BI (as applicable)

Optional: dbt / Airflow / Cloud Storage / Sheets automation / APIs