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Mid-level, generalist senior title but niche Coveo expertise reduces candidate density.
Specialized Coveo/search-platform and eCommerce merchandising experience limits cross-industry transferability.
Mandates 6+ years and specific Coveo, AWS, Snowflake, and search-merchandising expertise, increasing shortlisting rigidity.
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Own the technical implementation and optimization of Coveo search integrations, query pipelines, AI/ML model configurations, merchandising rules, and data ingestion pipelines across multiple digital platforms (Agilent.com, Community, eCommerce).
Collaborate with cross-functional teams (experience, content, commerce, data, analytics, platform) to ensure search delivers relevant, permission-aware, measurable, and scalable customer experiences.
Analyze search analytics and data to continuously improve search relevancy, content discoverability, and customer self-service outcomes.
Bachelor's or master's degree in Computer Science, Engineering, Information Systems, Data Engineering, or equivalent practical experience.
6+ years of software engineering experience with search platforms, digital commerce, content platforms, data integrations, or enterprise web applications.
Hands-on experience with Coveo platform capabilities including sources, indexes, query pipelines, search APIs, analytics, permissions, and AI/ML model configuration.
Experience with AWS-based ETL and data engineering (S3, Glue, Lambda, Step Functions, EventBridge) and programming in JavaScript/TypeScript, Python, Java, or similar languages.
Experienced with end-to-end Coveo implementations for both commerce and content search including query pipeline design, model tuning, merchandising, and analytics integration.
Skilled in integrating Coveo analytics with enterprise data platforms like Snowflake to enhance KPIs and relevancy monitoring.
Proficient in designing scalable AWS ETL data pipelines for search ingestion, metadata enrichment, permissions, and incremental synchronization in production environments.