Salesforce · salesforce.wd12.myworkdayjobs.com · checked today
Architect, Data Platform — AgentExchange
Skills, with evidence
- Data modelling
Deep architecture experience in at least three of : lakehouse / warehouse design, streaming + batch pipelines, dimensional and event modeling, feature stores, model serving.
must have - Streaming
Pipelines and contracts. Streaming and batch ingestion, schema governance, data contracts enforced across every AgentExchange engineering team, and pipeline reliability SLOs.
must have - Governance & security
Data security and governance as a first-class skill: PII classification, multi-tenant isolation, fine-grained access control, GDPR / CCPA, lineage and audit, and the security implications of LLM / agent access patterns.
must have · not practised here - Machine learning
ML platform. Feature store, training and serving infrastructure, evaluation, and monitoring.
must have · not practised here - Data quality
Partner-facing dashboards refresh on a documented SLO, and instrumentation completeness is measurable and enforced.
must have - AWS
Cloud-native data infrastructure: Snowflake, BigQuery, Redshift, or Databricks; AWS-based platforms.
must have · not practised here - Dashboards & BI
Own the data and intelligence architecture for AgentExchange — the marketplace where partners list, sell, and operate Agentforce, MuleSoft, Tableau, and Slack solutions.
not practised here - Failure handling
Feature store, training and serving infrastructure, evaluation, and monitoring.
- Cost & performance
LLM systems experience, in production: RAG, embeddings and vector stores, prompt and context engineering, offline and online evaluation, cost and latency tuning, hallucination and safety controls.
- SQL
Cloud-native data infrastructure: Snowflake, BigQuery, Redshift, or Databricks;
- Schema evolution & contracts
Streaming and batch ingestion, schema governance, data contracts enforced across every AgentExchange engineering team, and pipeline reliability SLOs.
- Spark
Cloud-native data infrastructure: Snowflake, BigQuery, Redshift, or Databricks;
- Warehousing
Deep architecture experience in at least three of : lakehouse / warehouse design, streaming + batch pipelines, dimensional and event modeling, feature stores, model serving.
- GCP
Cloud-native data infrastructure: Snowflake, BigQuery, Redshift, or Databricks;
not practised here
Your plan
- SQL
drills at the Staff level
- Modelling
drills at the Staff level
- Pipelines
drills at the Staff level
- Spark
drills at the Staff level
The full plan, drill by drill, is on the job page.
leaves in 8 dremoved the moment Salesforce closes it