Marketing Analytics Engineer, Data Products & Activation
Listed on 2026-08-13
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Marketing / Advertising / PR
Digital Marketing -
IT/Tech
Digital Marketing
A Little About Us
At Zelis, we Get Stuff Done. So, let’s get to it!
Zelis is modernizing the healthcare financial experience across payers, providers, and healthcare consumers. We serve more than 750 payers, including the top five national health plans, regional health plans, TPAs and millions of healthcare providers and consumers across our platform of solutions. Zelis sees across the system to identify, optimize, and solve problems holistically with technology built by healthcare experts – driving real, measurable results for clients.
At Zelis, AI is woven into the fabric of how we work. Every associate is expected - and empowered - to partner with AI to challenge the status quo, accelerate innovation, and amplify their impact. This is a place for builders with a growth mindset who act with agility, embrace change, and use modern technology to shape smarter solutions, exceptional experiences, and the future of our industry for our clients, customers, and our culture.
Little About You
You bring a unique blend of personality and professional expertise to your work, inspiring others with your passion and dedication. Your career is a testament to your diverse experiences, community involvement, and the valuable lessons you've learned along the way. You are more than just your resume; you are a reflection of your achievements, the knowledge you've gained, and the personal interests that shape who you are.
Position OverviewZelis is seeking a Marketing Analytics Engineer, Data Products & Activation to help build the next generation of marketing data, AI, and activation capabilities. This role will translate marketing, website, sales, CRM, paid media, and engagement signals into governed marketing data products that support audience intelligence, journey analytics, segmentation, personalization, lead qualification, attribution, sales activation, DXP experiences, and AI-enabled decisioning. The role will help mature Snowflake from campaign-specific tables and manual activation logic into reusable, trusted, and activation-ready data products, including Golden Account, Golden Contact, Segment Membership, Product Interest / Intent, Persona, Buying Committee Role, Consent / Suppression Eligibility, Engagement Score, Intent Intensity, Opportunity Context, Product Ownership, White-Space Opportunity, and Next-Best-Product Candidate.
The ideal candidate combines analytics engineering, marketing technology fluency, web data architecture, data product discipline, and AI context-layer design.
- Design, build, and maintain analytics-ready and activation-ready marketing data products in Snowflake that support digital marketing, website engagement, audience segmentation, journey progression, lead qualification, attribution, personalization, DXP experiences, and sales activation.
- Co‑own the marketing data product lifecycle, including definitions, source systems, transformation logic, data contracts, refresh cadence, quality thresholds, lineage, downstream consumers, activation destinations, change control, and known limitations.
- Help define and maintain the canonical marketing data model across Snowflake, Hub Spot, Salesforce, DXP, paid media, reporting, and activation platforms, including shared definitions for MQL, lifecycle stage, product interest, persona, buying committee role, consent status, suppression eligibility, engagement, and intent.
- Convert one‑off audience requests and campaign list logic into reusable segment data products with documented purpose, inclusion logic, exclusion logic, suppression rules, QA checks, refresh cadence, activation destinations, business owner, technical owner, and success metrics.
- Build and manage governed AI context layers that make marketing data usable by LLMs, AI assistants, and agentic workflows, including curated metric definitions, audience attributes, content taxonomy, campaign metadata, web behavior signals, journey states, data lineage, approved business rules, confidence scores, and review thresholds.
- Develop data structures that connect website behavior to known and unknown audience profiles, including page views, content engagement, form interactions,…
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