Data Engineer I
$91kBertelsmann-Jobs
Job Description The Revenue Technology Data Engineer I owns the revenue data platform that powers analytics and AI across the customer lifecycle. This role designs and operates ingestion pipelines from Salesforce and other RevTech systems (e.g., Gong, Pardot) into Salesforce Data Cloud (Data 360), builds and maintains identity resolution and data models within Data Cloud, integrates third‑party enrichment sources, interoperates with the Relias Information Hub on Databricks, onboard new structured and unstructured sources, and prepares the trusted, governed data foundation that grounds our Agentforce agents. You will partner with Revenue Technology colleagues, the Salesforce architecture team, and central data engineering to translate business needs into reliable data products.
WHAT YOU’LL BE DOING
Data Cloud Pipeline Development: Design, build, and maintain ingestion and transformation pipelines into Salesforce Data Cloud (Data 360) from Salesforce CRM, Gong, Pardot (MCAE), and other revenue systems using native connectors, APIs, and streaming patterns. Data Modeling and Identity Resolution: Build and maintain Data Cloud data models, mapping to the canonical data model, and configure identity resolution rulesets to unify customer and account data across sources. AI and Agentforce Enablement: Prepare, structure, and govern the data foundation that grounds Agentforce, including unstructured sources, so agents operate on accurate, current, and permissioned data. Cross‑Platform Integration and Enrichment: Integrate Data Cloud with the Relias Information Hub on Databricks, and integrate and maintain enrichment pipelines from providers such as ZoomInfo, Dun and Bradstreet, Definitive Healthcare, and Clay into Salesforce and Data Cloud, including match and dedupe logic, field survivorship, and monitoring of match rates and data freshness. Data Quality, Governance, and Troubleshooting: Ensure data accuracy, consistency, lineage, and security through validation, monitoring, and access controls, and identify, diagnose, and resolve data issues promptly. Documentation: Create and maintain documentation for pipelines, data models, mappings, and integration patterns.QUALIFICATIONS
Bachelor’s Degree in computer science or related field 2+ years in data engineering, with at least 1 to 2 years on Salesforce Data Cloud or comparable CDP and Salesforce data integration. Hands‑on experience with Salesforce Data Cloud (Data 360): data streams, connectors, ingestion, transforms, data model objects, identity resolution, and calculated insights. Working knowledge of the Salesforce platform and revenue stack data structures (Salesforce CRM, Gong, Pardot/MCAE). Programming in SQL and Python.IN OFFICE REQUIREMENT
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