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Medium—niche Coveo expertise narrows applicants despite a mid-level, visible engineering title.
High—requires specialized Coveo search, eCommerce merchandising, and analytics-focused data engineering skills.
High—explicit 6+ years and mandatory Coveo, AWS, and Snowflake experience required.
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Own and implement Coveo search integrations, query pipelines, analytics, and AI/ML models to enhance customer discovery and self-service across Agilent platforms.
Design, build, configure, and optimize eCommerce and content search use cases including merchandising, relevance tuning, and data ingestion using AWS-based pipelines.
Collaborate with cross-functional teams to continuously improve search relevance, user experience, and measurable customer outcomes.
Bachelor’s or master’s degree in Computer Science, Engineering, Information Systems, Data Engineering, or equivalent experience.
6+ years of software engineering experience with search platforms, digital commerce, content platforms, or enterprise web applications.
Hands-on experience with Coveo platform including sources, indexes, query pipelines, APIs, analytics, machine learning models, and search integrations.
Experience with AWS ETL and data engineering services (S3, Glue, Lambda, Step Functions) and programming skills in JavaScript/TypeScript, Python, Java, or similar languages.
Experienced in both commerce and content search with deep Coveo implementation skills including query pipeline design, analytics integration, and AI/ML model tuning.
Skilled at leveraging analytics (including Snowflake integrations) to drive search relevance and customer self-service improvements.
Proven ability to design and operate scalable AWS data ingestion pipelines supporting search indexing and incremental updates in enterprise environments.