Position : Senior Associate, Data Analytics - Implementation Specialist
Location : Hybrid (3 days onsite) Toronto
Duration : 6 Months (extendable)
Overview
Joining a world class Data Analytics capability centre of excellence you will be responsible for working with our Fortune 500 clients designing, configuring and implementing cross-platform analytics data models across web and native mobile applications.
You will leverage platforms such as Firebase, GA4, Google Tag Manager and Google Measurement Protocol to configure analytics data collection across multiple platforms.
You will ensure best practices are followed through the implementation lifecycle and help construct data sets for Google Analytics / GA4 for use by our team, our clients as well as other stakeholders.
You will be part of a large digital analytics specialist team delivering analytics implementation, reporting, and analysis while also having the opportunity to collaborate with other colleagues from the global data team.
Job Description
- Migrate clients using UA / GA360 to GA4, build implementation plans and developer guides. Leverage Adobe Launch, Google Tag Manager and Ensighten.
- Lead and architect technical vision for web analytics implementation, testing and reporting using Google marketing stack.
- Serve as the "Tagging Architect" by evolving and managing the solution design reference documentation which outlines analytics variables, rules, and use cases across web properties and applications
- Create, manage, and enforce digital analytics tagging standards to ensure robust and consistent data is captured for analysis.
- Experience with event based data model to deliver user-centric measurement
- Test and validate the implementation of Google Analytics (GA4) tagging changes throughout the development lifecycle
- Educate testing teams on the tools and methods to validate digital analytics tagging effectively
- Manage Google Analytics (GA4) configurations including data streams, enhanced measurements and data sources
- Leveraging analytics API’s like Google Analytics Data API and building automation tools for analytics reporting that includes platforms such as GA4, Google Data Studio or BI tools like Domo, Looker, Tableau etc.
- Support the training and adoption of GA4 across large enterprises.
- Strong client facing communication skills and attention to detail required Client Expectations
- Tagging plan creation : Leverage an Adobe Analytics tagging plan provided by ED&A to build / reference for the creation of a GA4 tagging plan.
At a high-level, GA4 tagging plans generally include : Events, Dimensions, Metrics, User Properties & Ecommerce.
- Data Validation : Leverage developer tools such as the Chrome Dev console, Omnibug, or Adobe Experience Manager to perform onsite debugging / validation of tags.
- In-platform validation of processed data will also need to occur after data is collected.
- LOB / DPM relationship management : Emails, working sessions, platform demos, presentations etc.
- Reporting : Collaborate with LOB partners to create LookerStudio dashboards or GA4 exploration reports that provide actionable insights.
- Project Management : Provide regular updates as to the operationalization status of GA4 for LOBs the resource manages or tickets assigned to them.
Qualifications
- 3+ years of experience in digital marketing / data analytics space
- 3+ years working with Google Analytics 360 suite with an excellent understanding of digital analytics tagging best practices.
Experience with GA4 implementation a definite plus
- 3+ years experience in delivering E2E data analytics implementation lifecycle (requirements, solution design, tagging, configuring, I / O, reporting and dashboarding) for retail (preferred) or any other industry vertical
- 2+ years experience working with tag manager tools such as Google Tag Manager, Tealium IQ, Adobe Launch, Ensighten
- Hands-on experience working on 3rd party tracking implementations using tag manager templates.
- Experience working with jQuery, Regular Expressions, HTML CSS selectors is beneficial
- Knowledge of Python / Google BigQuery architecture will be an added advantage
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