4+ years hands-on experience in data engineering, CDP, or customer-data platforms; experience with Salesforce Data Cloud preferred
Proven track record building ingestion pipelines, identity resolution, and segment models
Experience integrating Salesforce with Snowflake, S3, APIs, streaming platforms (Kafka/Kinesis) and ETL/ELT tooling
In-depth knowledge of Salesforce architecture flows, Service Cloud, CRM, Data Cloud
Deep SQL skills and knowledge of data modeling (event and profile models)
Strong with data pipeline tooling and orchestration (e.g., Airflow, dbt, Mulesoft); familiarity with Snowflake/BigQuery preferred
Responsibilities
Data Architecture & Ingestion — Design and operate Data Cloud data models, ingest pipelines, and real-time streaming for customer, vehicle, product, and telematics data. Own connectors (Salesforce sources, Snowflake, S3, APIs), transformation logic, identity resolution rules, and orchestration to deliver production-ready datasets. Ensure lineage, observability, and SLAs for data delivery
Identity Resolution & Data Governance — Implement and tune identity stitching/resolution to create trusted, unified profiles. Apply data governance, PII masking, retention policies, and role-based access so data is compliant and usable across Sales, Service, and Marketing
Analytics, Segments & AI Enablement — Build customer/vehicle segments, event models, and data views that power dashboards, Einstein models, and AI use cases (predictive maintenance, propensity models, real-time offers). Partner with analytics and AI teams to productionize models and monitor model drift
Integration & Automation (DataOps) — Implement CI/CD for data pipelines, automate deployments of mappings and ingest jobs, and manage pipeline retry/reconciliation strategies. Collaborate with platform engineering on secure, scalable environments (Snowflake, Kafka, Mulesoft or equivalent)
Stakeholder Enablement & Continuous Improvement — Lead workshops with business stakeholders to translate business outcomes into Data Cloud solutions. Produce clear documentation, runbooks, and training; sponsor pilots and POCs to advance data-driven products