Marketing Analytics Engineer, Data Products & Activation

Marketing Analytics Engineer, Data Products & Activation

Zelis 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.

What You'll Do

• 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, conversion events, source attribution, session behavior, identity resolution inputs, and downstream Salesforce CRM outcomes.
• Partner with Digital Experience, Marketing Automation, Paid Media, Sales Operations, Revenue Operations, Legal / Compliance, Analytics, and Enterprise Data teams to define event-streaming, governance, and activation requirements from  and related digital properties into Snowflake.
• Create durable data models that support identity resolution, golden account/contact attributes, engagement scoring, buyer-group intelligence, product interest history, lifecycle movement, product ownership, opportunity context, consent status, suppression logic, and channel eligibility rules.
• Build reusable activation datasets and reverse ETL requirements that send trusted, explainable, consent-safe data from Snowflake into downstream marketing destinations, including email automation, CRM, paid media, digital experience, and journey orchestration platforms.
• Establish data quality checks, reconciliation logic, monitoring routines, product SLAs, and exception handling for marketing data products, with emphasis on website events, campaign metadata, lead lifecycle data, audience membership, consent / suppression eligibility, identity confidence, and activation outputs.
• Support predictive lead qualification, intent scoring, attribution, MQL value, expansion opportunity, and next-best-action work by building clean feature tables, training-ready datasets, model output tables, and explainability-ready structures.
• Use AI-assisted development and analytics techniques to accelerate SQL generation, documentation, data testing, anomaly detection, metadata tagging, and first-pass data product design, while maintaining human review, governance, and quality standards.

What You'll Bring to Zelis

• 6+ years of experience in analytics engineering, data engineering, marketing analytics engineering, marketing technology, digital analytics, Rev Ops analytics, or a related technical analytics role.
• Advanced SQL experience and demonstrated ability to build reliable, reusable data models in Snowflake or comparable cloud data warehouse environments.
• Experience translating business requirements into production-quality data products, including source-to-target mapping, transformation logic, QA routines, data contracts, metric definitions, documentation, lineage, and stakeholder enablement.
• Strong understanding of B2B marketing data, including campaign metadata, website behavior, audience segmentation, lead lifecycle, form conversion, CRM outcomes, paid media signals, sales funnel data, opportunity context, buying committees, product interest, and expansion…