Informatica Cloud Account Executive, Data Integration

Salesforce Salesforce · Enterprise · New York, NY +5

Salesforce is seeking an Informatica Cloud Account Executive specializing in Data Integration. This role focuses on selling data integration solutions that enable modern AI and Analytics, helping enterprises modernize ETL environments and build high-performance data fabrics. The AE will partner with Core AEs to drive integration outcomes, act as a technical sales authority on cloud ecosystems, and align Informatica's roadmap with clients' AI and data engineering strategies. Understanding of GenAI data readiness and its impact on RAG and LLM performance is crucial.

What you'd actually do

  1. Achieve a dedicated quota for Data Integration products by identifying and closing complex opportunities.
  2. Act as a technical sales authority on Cloud Ecosystems (AWS, Azure, GCP, Snowflake, Databricks, etc.), articulating how Informatica's IDMC provides the critical connectivity and performance layer for multi-cloud architectures.
  3. Lead deep-dive discovery sessions to qualify high-volume data movement use cases, including Legacy ETL-to-Cloud migrations, Real-time Streaming, and API-led integration.
  4. Drive forecasting accuracy and pipeline generation for Data Integration.
  5. Partner with Chief Data Officers and Enterprise Architects to align Informatica’s integration roadmap with their long-term AI and data engineering strategies.

Skills

Required

  • Data Integration
  • iPaaS
  • ETL solutions
  • Cloud Ecosystems (AWS, Azure, GCP, Snowflake, Databricks)
  • Data Engineering pipelines
  • Cloud Data Warehousing migration strategies
  • GenAI data readiness
  • RAG
  • LLM performance
  • Sales acumen
  • Technical depth
  • Communication skills
  • Presentation skills

Nice to have

  • Experience with Intelligent Data Management Cloud (IDMC)
  • Experience with Real-time Streaming
  • Experience with API-led integration

What the JD emphasized

  • 7+ years of experience selling Data Integration, iPaaS, or complex ETL solutions.
  • Understanding of GenAI data readiness, specifically how high-quality data integration fuels RAG (Retrieval-Augmented Generation) and LLM performance.