Lead Analytics Engineer Clickstream-MarTech

Lead Analytics Engineer Clickstream

Location: Chicago, IL (2 3 days onsite required)

Duration:6+ Month

MOI: Skype

Required:

Must-Have:

• Strong clickstream analytics experience
• Hands-on experience with event instrumentation and digital journey tracking
• Deep experience with web/app tracking and event-based data

Very Nice to Have:

• Retail or Food industry experience

Role Summary:
We are looking for a Lead Analytics Engineer with strong experience in clickstream, event instrumentation, and digital analytics implementation to build and scale customer behavior tracking across web and app platforms. The role focuses on designing event schemas, CDP integrations, and activation pipelines using mParticle, Mixpanel, and paid media ecosystems.

Key Responsibilities:

• Lead clickstream and event tracking implementation across web and digital touchpoints
• Design and manage event schemas, identity resolution, and data quality in mParticle/Mixpanel
• Partner with product, CX, and analytics teams to translate requirements into scalable tracking solutions
• Enable funnel analysis, conversion tracking, and customer journey measurement
• Build and activate paid media audiences via CDP integrations such as Meta, Google, TikTok, and DV360
• Troubleshoot tracking, SDK, API, and data discrepancies
• Provide technical leadership, code reviews, and documentation

Qualifications:

• 6 10 years in analytics engineering, MarTech, or digital analytics implementation
• Strong hands-on experience with clickstream data, event instrumentation, and CDPs
• Experience with SDKs, tagging frameworks, identity management, and data contracts
• Working knowledge of Node.js or PHP (Laravel); basic React understanding preferred
• Familiarity with AWS/Google Cloud Platform and modern deployment practices
• Experience with paid media activation and MarTech integrations
• Strong problem-solving and cross-functional collaboration skills

Additional Must-Have Experience:

• Adobe Analytics
• Google Analytics
• End-to-end analytics solution design
• Digital platforms, customer journeys, and KPI understanding

Profiles to Avoid:

• Mainly SQL / ETL / data modeling profiles
• Data lake / Databricks / infrastructure-heavy candidates
• Generic data engineering or platform engineering backgrounds