Senior Analytics Support Engineer

About the Role

We are looking for a skilled and detail-oriented Analytics Support Engineer to join our team. The ideal candidate will bring hands-on expertise in Google Analytics 4 (GA4), Google Tag Manager (GTM), Looker, and Tableau, along with solid technical knowledge in Python, SQL, and AWS infrastructure.
You will play a critical role in managing analytics implementations, data pipelines, and reporting solutions to empower business decisions with accurate, actionable insights.

Key Responsibilities

• Implement and maintain tracking solutions using GA4 and Google Tag Manager.
• Develop, manage, and optimize data visualizations and dashboards in Looker and Tableau.
• Write efficient SQL queries for data extraction, transformation, and validation.
• Collaborate with cross-functional teams to troubleshoot data issues and ensure data accuracy and integrity.
• Build and maintain Python scripts for data automation, analysis, and reporting.
• Support data pipelines and ETL processes in AWS environments (e.g., S3, Lambda, Redshift).
• Monitor analytics configurations, tag deployments, and conversion tracking to ensure reliable data flow.
• Provide documentation, training, and support to stakeholders on analytics tools and reporting platforms.

Required Skills & Qualifications

• Bachelor's degree in Computer Science, Data Analytics, or a related discipline.
• 5+ years of experience in analytics or data engineering/support roles.
• Proven experience with Google Analytics 4 (GA4) and Google Tag Manager (GTM).
• Strong command of Looker and/or Tableau for building advanced dashboards and visualizations.
• Proficiency in Python and SQL for data manipulation and automation.
• Experience working within AWS infrastructure (e.g., S3, EC2, Lambda, Redshift).
• Deep understanding of data governance, tracking architecture, and web analytics best practices.
• Strong analytical thinking and problem-solving abilities.
• Excellent communication and stakeholder management skills.
• Preferred Skills
• Familiarity with BigQuery, redshift, or other cloud data warehouses.
• Experience integrating marketing and product analytics tools.
• Understanding of APIs and data ingestion frameworks.