Data Analytics & Optimization Manager

Key Responsibilities:

BigQuery Expertise: Leverage Google BigQuery to manage, query, and optimize large-scale analytics datasets for actionable business insights.

SQL Proficiency: Develop, maintain, and optimize complex SQL queries to support reporting, dashboards, and ad hoc analysis.

Data Tracking & Tagging: Oversee tagging and tracking accuracy using analytics platforms (Google Analytics, GA4, Adobe Analytics, etc.), tag management systems (e.g., Google Tag Manager), and pixel implementations and provide improvement recommendations.

Reporting & Insights: Analyze digital performance data, prepare regular dashboards, and communicate actionable insights for continuous improvement. Assist with ad-hoc reporting requests by building explorations and reports in GA4

Optimization Initiatives: Manage A/B and multivariate testing programs. Build test plans for A/B testing, multivariate testing, segment-based targeting, behavioral targeting and personalization. Use JavaScript and jQuery for custom tagging, data layer manipulation, and supporting website experiments.

User Journey Analysis: Conduct funnel analyses, heat mapping, user flow, and behavioral studies to identify drop-offs and friction points.

Collaboration: Advise designers, developers, and marketers on data-driven optimization recommendations, supporting new campaigns and website updates. Work alongside development teams to diagnose and troubleshoot technical issues, ensure proper content display, and properly manipulate JavaScript, HTML and CSS. Collaborate with various business stakeholders in scoping outanalytics implementations for new initiatives

Attribution Modeling: Guide the business in understanding digital attribution, channel performance, and multi-touch journey contributions.

Tool Ownership: Maintain and optimize web analytics tech stack, recommending new tools or approaches as necessary.

Compliance: Ensure data collection and processing adhere to privacy regulations (GDPR, CCPA, etc.).

Required Skills:

• GoogleAnalyticsimplementation experience across the lifecycle.
• Proven ability to design, write, and optimize advanced SQL queries, with deep experience using Google BigQuery to extract and analyze insights from complex datasets.
• Solid understanding of web analytics tools such as Google Analytics or Adobe Analytics.
• The candidate should be very well versed with Google Tag Manger or an equivalent tag management solution
• Thorough knowledge of reporting console and admin console
• Hands-on experience with one or more debugging tools like Charles, Chrome Debugger, or an equivalent solution
• Hands-on experience implementing marketing automation platforms and forms (e.g., Pardot, Eloqua, Hubspot) with websites
• Hands-on experience in implementing and maintaining 3rd party or tracking pixels such as Google gTag, Facebook Pixel, Linked Insight tags, etc.
• Excellent JavaScript experience in coding and troubleshooting theanalytics implementation on a given site.
• Solid understanding of website and campaign optimization, including A/B, multivariate testing
• Generate optimization plans based on business and customer goals, analytics and best practices.
• Experience with testing and optimization tools(e.g., AdobeTest & Target, Optimizely)
• Experience in building Solution Design Reference (SDR) documents based on requirements from stakeholders
• Be able to convert SDR to exact JS code to be added on page or user actions on page
• Strong written and spoken communication skills with the ability to efficiently translate business to technical requirements, and educate stakeholders on best practices and results
• Ability to manage stakeholders, prioritize requests and organize a roadmap for the backlog of requests
• Critical thinker who strives to improve the analytics and optimization program
• Proactive attitude to determine areas for improvement and the ability to influence change across different stakeholders
• Familiarity with the dependencies between a content management system (CMS)and reporting tools, including data warehousing platforms (e.g., Redshift, BigQuery, or Snowflake is a plus)