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VBeyond Corporation · 1 day ago

Databricks Integration Architect with the Google Ads

Texas, United States

Contract

Hybrid

Senior Level, Lead/Staff

12+ years exp

VBeyond Corporation is seeking a Sr. Data & Integration Architect to build and maintain marketing data pipelines and integrate various platforms such as Sitecore and Salesforce. The role involves ensuring data governance and enabling AI-driven analytics for personalized buyer journeys.

ConsultingCRMDeliveryHuman ResourcesInformation Technology

Hiring Manager

Prashant P

Responsibilities

Design and maintain data pipelines that ingest, transform, and model marketing and engagement data in Databricks or similar environments

Build connections across Sitecore, Google Marketing Platform, 6sense, LinkedIn, Salesforce, and other digital systems to enable end-to-end visibility into the buyer journey

Partner with IT and data teams to align marketing data with enterprise standards for governance, quality, and security

Develop unified data models linking engagement, content consumption, account signals, and opportunity data to support analytics and journey-based insights

Partner with the Martech team to ensure that all marketing platforms are configured and documented in ways that support analytics and AI applications

Define and communicate data capture standards, tagging requirements, and event tracking structures needed for visibility across the buyer journey

Create and maintain data dictionaries, taxonomies, and schemas that ensure analytics receives consistent and usable data

Act as the primary liaison between analytics and Martech teams to translate analytical and modeling needs into data requirements for platform setup and integrations

Conduct data audits to validate that critical events, attributes, and identifiers are captured and aligned across systems

Define and maintain frameworks for capturing and structuring web behavior, personalization events, and user interactions within Sitecore and related systems

Ensure engagement signals and content interactions can be tied to known accounts and individuals for journey analysis and personalization

Support analytics in using web data to uncover buying stage patterns and trigger tailored recommendations

Partner with marketing AI specialists to ensure data structures support advanced use cases such as: Buyer journey stage prediction, Next-best-action and next-best-content modeling, Audience and account-level engagement scoring, Personalized experience and content recommendation frameworks

Design and maintain data pipelines that make behavioral and engagement data AI-ready

Ensure all marketing data can be connected and contextualized for AI-driven analysis

Evaluate and implement emerging technologies that enhance marketing’s ability to predict, personalize, and optimize engagement

Qualification

DatabricksSparkSQLPythonGoogle AnalyticsSitecore PersonalizationData governanceSalesforce integrationDigital marketing data structuresCloud platformsAI/ML use casesData visualization toolsEmerging technologiesCollaboration