Web Analytics Engineer

Overview We are seeking an experienced Analytics Engineer to join our innovative Fintech team. This role focuses on building scalable data pipelines, integrating Google Analytics (GA4) / Google Tag Manager, and delivering actionable insights through Looker Studio dashboards. You will set‑up and manage financial marketing data in BigQuery to support marketing teams in making data-driven decisions. This position requires strong client-facing experience, as you will collaborate directly with external stakeholders to understand requirements, deliver solutions, and ensure client satisfaction. Key Responsibilities Design and maintain data pipelines and ETL processes using BigQuery for high-volume financial marketing data. Integrate Google Analytics (GA4) data with other data sources to track user behavior, conversion funnels, and product performance. Create and manage web analytics tracking framework across a variety of third‑party web applications. Build and optimize Looker Studio dashboards for KPIs such as CPA, LTV, and full‑funnel metrics. Ensure data accuracy, governance, and security in line with financial regulations. Work directly with external clients to gather requirements, present insights, and provide technical guidance. Collaborate with internal teams (platform, marketing, risk) to deliver actionable insights. Required Skills & Qualifications 3+ years of experience in web analytics engineering or data engineering. Strong proficiency in BigQuery and SQL for large-scale data processing. Hands‑on experience with Google Analytics (GA4)/Google Tag Manager or Adobe Analytics including a high degree of customization (e.g., custom variables, segments, filters, and event tracking). Expertise in Looker Studio, Tableau, Power BI, or Domo for creating interactive dashboards. Proven experience in client‑facing roles, including requirements gathering and solution delivery. Knowledge of data privacy and compliance standards in financial services. Preferred Qualifications Experience creating/testing AI/ML predictor models (e.g., XGBoost, K‑Means Cluster Analysis) with web analytics data. Experience integrating internal data sources with web analytics in secure methods. Experience in Fintech analytics. Experience with integrating third‑party data sources (e.g., Snowflake, AWS RDS/DynamoDB, Azure SQL, MySQL). Familiarity with Python or R for advanced analytics. Exposure to Google Cloud Platform and ETL tools. Experience creating embedded dashboards with JavaScript charting libraries. Education Bachelor’s degree in Statistics, Data Analytics, Computer Science, AI, Finance, or related field. #J-18808-Ljbffr SupportFinity™