Software Engineering PMTS - Data Platform
Salesforce1 day ago
Base Salary
$197k - $345k/yr
Responsibilities
- Own the canonical data model, destination consolidation, telemetry taxonomy, and 18-month AgentExchange data platform roadmap.
- Architect streaming and batch ingestion, schema governance, cross-team data contracts, and pipeline reliability SLOs.
- Deliver self-service partner and marketplace analytics using Data 360 and Tableau Next.
- Sponsor feature-store, model-training, model-serving, evaluation, and monitoring infrastructure and predictive marketplace models.
- Architect MCP-based agent data access, RAG, embeddings, vector-store strategy, LLM evaluation harnesses, and safety guardrails.
- Set standards for PII handling, tenant isolation, fine-grained access, GDPR/CCPA compliance, lineage, audit, and LLM data privacy.
- Represent data architecture in cross-organizational reviews and align Platform Services, Search & Personalization, and Partner Experience teams.
- Lead migration of existing data pipelines without production disruption.
- Mentor the Data Engineering & Analytics organization and develop senior individual contributors.
Requirements
- 10+ years of software or data engineering experience, including multi-year ownership of an enterprise-scale data or ML platform.
- Deep architecture experience in at least three areas including lakehouse or warehouse design, streaming and batch pipelines, dimensional and event modeling, feature stores, and model serving.
- Experience with cloud-native data infrastructure, including Snowflake, BigQuery, Redshift, or Databricks on AWS-based platforms.
- Production experience with RAG, embeddings and vector stores, prompt and context engineering, LLM evaluation, cost and latency tuning, and hallucination and safety controls.
- Working knowledge of MCP or equivalent tool and agent protocols, with a clear approach to exposing data safely to agents.
- Expertise in PII classification, multi-tenant isolation, fine-grained access control, GDPR/CCPA, lineage, audit, and LLM/agent access security.
- Experience representing a technical domain in cross-organizational architecture forums and influencing teams without direct management authority.
- Strong executive communication skills, including presenting architecture trade-offs to technical and product stakeholders.
- Related technical degree required.
- Preferred experience with Salesforce Data 360, Tableau Next, Slack, MuleSoft data integration, marketplace or e-commerce data, large-scale migrations, NPS and effort-score measurement, privacy-preserving ML, agent evaluation frameworks, LLM observability, and Salesforce Platform features.
Benefits
- In-office expectation of 10 days per quarter to support customers and collaborate with teams.
- Benefits include time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program.
Tech Stack
Categories
Data EngineeringML Engineering
About Salesforce
Salesforce builds cloud-based customer relationship management software and a broader Customer 360 platform for sales, service, marketing, commerce, and analytics, sold by subscription to businesses and public-sector organizations. Founded in 1999 and headquartered in San Francisco, it trades on the NYSE under the symbol CRM. Its portfolio includes Sales Cloud, Service Cloud, Marketing Cloud, MuleSoft integration, Tableau analytics, and Slack for collaboration, with extensive developer tools and APIs.