Senior Digital Analytics Engineer - Customer Experience

Sherwin-Williams•Cleveland, OH

1d•Onsite

About The Position

We are seeking a highly analytical and technically skilled Senior Digital Analytics Customer Experience (CX) Engineer to join our Global Digital Analytics Customer Experience (CX) team, supporting the Performance Coatings Group’s digital initiatives. This role is responsible for designing, implementing, and optimizing digital data collection strategies across websites, applications, and digital marketing channels. The ideal candidate brings deep experience in digital analytics, strong data engineering and data governance expertise. This candidate is expected to use these skill sets to help elevate customer experiences, build a foundation for personalization and digital marketing activation, and drive business growth. As a senior member of the team, this person will play a critical leadership role in ensuring data quality, standardization, and connectivity across digital platforms, while advancing our measurement framework, analytics automation, and predictive insights capabilities.

Requirements

Must be at least eighteen (18) years of age
Must be legally authorized to work in the country of employment without needing sponsorship for employment work visa status now or in the future
Must have a bachelors degree or higher
Have at least two (2) years of experience in leadership role(s), supervising others or leading teams
Must have five (5) years of experience in digital analytics engineering, analytics implementation, web measurement, or marketing data engineering roles.
Must have strong hands-on expertise with digital analytics platforms such as Adobe Analytics, Adobe Customer Journey Analytics, or Google Analytics 4
Must have advanced proficiency with tag management systems (Adobe Tags, Google Tag Manager).
Must have experience designing and managing data layers, SDRs, and tagging governance frameworks.
Must be proficient in SQL for data extraction, transformation, and automation.
Must understand A/B testing platforms and experimentation (e.g., Adobe Target)

Nice To Haves

Have a bachelor's degree or higher in Business, Marketing, Analytics, Data Science, Statistics, Mathematics, or Computer Science
Be familar with cloud and data engineering environments such as Snowflake or Databricks
Have experience with Tableau, Power BI, or other BI platforms

Responsibilities

Enable Personalized Digital Customer Experiences through Data Collection & Connectivity
Digital Data Collection, Tagging, and Implementation
Partner with digital analysts and IT to enable insights generation for marketing, product, and digital teams through reliable, well‑structured data and tagging strategies (Adobe Analytics, Adobe Customer Journey Analytics, Google Analytics)
Partner closely with development teams, conduct thorough QA and user acceptance testing (UAT) for analytics tags, data layer updates, and new digital customer experiences.
Lead digital tagging strategy, implementation, and validation using enterprise tag management systems (e.g., Adobe Tags, Google Tag Manager).
Own and evolve the Solution Design Reference (SDR) documentation, ensuring alignment with business requirements and best‑practice analytics architecture.
Provide technical guidance on digital data layer design, event tracking, custom dimensions/variables, and tagging governance.
Data-Driven Customer Experience Personalization and Segmentation
Support A/B and multivariate testing with Adobe Target by establishing proper tagging, data validation, and measurement frameworks.
Build audience segments for digital marketing activation and personalization in Adobe or other digital platforms.
Data Engineering
Connect digital platforms and data by designing and maintaining scalable, automated data pipelines from digital marketing, analytics, and business intelligence platforms (e.g., Tableau)
Digital Data Governance & Quality
Champion enterprise data governance and quality standards across digital analytics platforms
Identify data gaps, inconsistencies, and duplication; drive improvements to increase data completeness, accuracy, and scalability.
Maintain and enhance naming conventions, taxonomies, standards, and data dictionaries for analytics assets.
Contribute to data hygiene routines including anomaly detection, validation processes, and automated quality checks.
Cross‑Functional Collaboration with Customer Experience Teams
Serve as a trusted technical advisor to marketing, ecommerce, digital products, and IT teams.
Communicate complex data concepts and implementation details to both technical and non‑technical audiences with clarity.
Provide mentorship and guidance to junior analysts and engineers, fostering growth and knowledge sharing across the team.