Overview

The Senior Analytics Implementation Specialist will provide advanced web and app analytics solutions and services to VML Data’s Tier one clients, enabling them to make informed, data-driven interactive strategy, product development, and personalization decisions.

The focus of this position is to leverage your advanced experience across both client-side and server-side analytics implementations, Customer Data Platforms (CDPs) like Rudderstack, and product analytics tools like Amplitude, alongside the Adobe Digital Experience Platform and Google Cloud Platforms. You will assist clients with the implementation, integration, and interpretation of their analytics solutions, ensuring robust data foundations that power AI/ML initiatives and advanced segmentation. This role demands high levels of interaction with clients, their technical teams, agencies, and partners.

This position is for self-motivated, entrepreneurial web and app analytics specialists with advanced knowledge of modern data stacks, privacy-centric tracking methodologies, and the ability to hit the ground running. The purpose of this role is to customize and provide solutions to clients’ exact business requirements and reporting needs, assist clients to implement proprietary and CDP-driven tracking code throughout their websites and mobile apps, and perform rigorous quality checks to ensure correct implementation and data integrity, in essence enabling them to answer complex business questions timely and accurately, and to fuel advanced AI/ML applications.

Responsibilities

• Advanced Analytics Implementation & Architecture:Lead enterprise-level implementation of digital analytics and CDP tools, including gathering business requirements, designing robust event schemas, managing server-side tracking implementations (e.g., using Google Tag Manager Server-Side or Rudderstack Event Streams), integration with various data destinations, custom coding, and enabling advanced reporting. This includes architecting solutions that support both traditional web analytics and modern product analytics (e.g., Amplitude & Google Analytics).
• Technical Expertise in Data Collection: Possess deep hands-on experience in website and mobile app tracking, including advanced tagging, event tracking, consent management platforms, and mapping complex customer journeys across touchpoints. Proficiency with Tag Management Systems (TMS), web technologies (HTML, CSS, JavaScript), mobile SDKs, and API integrations for server-side data collection is essential.
• Data Foundation for AI/ML:Design and implement data collection architectures that provide high-quality, comprehensive, and real-time data suitable for feeding Machine Learning (ML) models, Generative AI (LLMs), and advanced segmentation. Ensure data governance and privacy best practices are embedded in every implementation.
• Solution Architecture & CDP Integration:Design and implement holistic analytics and Customer Data Platform (CDP) solutions (Rudderstack focus, but aware of others like Segment) and system architecture that align with clients' enterprise-wide business needs and key performance indicators. This includes defining identity resolution strategies and leveraging CDPs for unified customer profiles.
• Adaptability, Curiosity, and Innovation:Adapt quickly to rapidly changing toolkits, emerging technologies (e.g., new AI/ML applications in analytics), and varied client engagements. Exhibit intense curiosity by generating proactive queries, investigating complex client questions, and exploring innovative data solutions for ad-hoc reporting and service excellence.
• Best Practices and Trend Analysis:Develop and champion best practices for privacy-centric data collection (e.g., server-side tracking to enhance data quality and compliance), track industry trends in AI-powered analytics, predictive modeling, and personalization using tools like Amplitude, and recommend solutions to enhance client capabilities and competitive advantage. Identify website and app improvements based on engagement, conversion, and traffic patterns, enriched by AI insights.
• Analytics System Management & Optimization:Support the daily management, maintenance, and optimization of clients' analytics systems and data pipelines, ensuring optimal tracking, data quality, and reporting efficacy. Create and maintain key reports, dashboards, and analyses, collaborating with internal teams for enhancements and leveraging AI-driven insights tools where applicable.
• Training, Education, and Thought Leadership:Develop and conduct training sessions covering all aspects of digital analytics, including modern data collection techniques, CDP functionality (Rudderstack), server-side tracking, and the application of AI/ML/LLM insights within analytics. Provide education for junior staff and internal teams to enhance awareness and knowledge, tailored to support the growth of client portfolios, and contribute to thought leadership.
• Quality Assurance, Data Validation, and Documentation:Oversee the development of detailed implementation documentation, data dictionaries, and rigorous quality assurance (QA) tests for tracking solutions, with particular emphasis on server-side validation and end-to-end data flow integrity, ensuring they meet expected standards and fuel reliable AI/ML outputs.
• Technology & AI Roadmaps:Stay informed about technology roadmaps, enhancements, and the rapid evolution of AI, ML, and LLMs in the analytics space. Evaluate new tools and techniques that can provide competitive advantages for our clients.
• Communication and Collaboration:Demonstrated ability to communicate effectively through oral, written, and visual methods, translating complex technical concepts (e.g., server-side architectures, AI/ML data requirements) into clear, actionable insights for technical and non-technical stakeholders. Work consultatively with clients and internal teams, building trust and delivering strategic advice.

REQUIREMENTS

• Minimum 5 years’ experience in web, app, and product analytics implementation and digital marketing.
• Strong Client-facing skills – responsive, results-driven, dedicated to customer support, and adept at consulting on complex technical and strategic data challenges.
• Strong attention to detail, excellent organization skills, and ability to work independently and manage multiple projects/responsibilities and small teams in a fast-paced environment.
• Exposure to enterprise-level clients and understanding of complex web/app ecosystems, privacy regulations (GDPR, CCPA), and best practices for data governance.
• In-depth knowledge and understanding of various client websites, mobile apps, their business models, and online marketing/product strategy.
• Strong knowledge/experience of modern marketing and product analytics tools, including:
• Analytics Tools: Google Analytics 4 (GA4), Adobe Analytics, Amplitude (essential for product analytics).
• Tag Management Systems (TMS): Google Tag Manager (GTM), Adobe Launch, Tealium iQ.
• Customer Data Platforms (CDPs): Rudderstack (strongly preferred), Segment, Tealium AudienceStream.
• Server-Side Tracking Platforms/APIs: Google Tag Manager Server-Side, Adobe Experience Platform Edge Network, Rudderstack Event Streams, Facebook Conversions API, TikTok Pixel API, etc.
• Data Layers: Designing and implementing robust, event-driven data layers (e.g., W3C Digital Data Layer), their definition, and implementation across web and app.
• Cloud Data Warehouses/Lakes: Google BigQuery (essential), Snowflake, AWS Redshift, Azure Synapse Analytics.
• Visual Analytics Platforms: Google Looker Studio (formerly Data Studio), Tableau, Power BI, Sigma Computing.
• A/B Testing / Optimisation / Personalisation: Adobe Target, Optimizely, Dynamic Yield, Google Optimize.
• AI/ML/LLM Concepts: Understanding of data requirements for machine learning models, basic familiarity with prompt engineering for analytical tasks, or experience with AI-powered insights tools within analytics platforms.
• Proficiency in JavaScript, HTML, CSS, and ideally familiarity with mobile SDKs (iOS/Android).
• Beneficial to have: Experience with Python or R for data analysis, advanced SQL skills, cloud platform certifications (GCP, AWS, Azure), and a foundational understanding of data science principles.

WPP Enterprise Solutions is committed to Employment Equity and transformation. In accordance with our Employment Equity objectives, preference may be given to candidates from designated groups.

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