Senior Data Engineer - Real-Time AI Data Architect

Enboarder; Ciudad de México; On-site; MXN 900,000 - 1,300,000; Full time

Job summary

Salesforce seeks a Senior Data Engineer to join the Data & Analytics organization and build scalable data pipelines and graphs powering its AI-driven agentic customer interactions. You will bridge raw data systems and the agentic layer, grounding AI agents in real-time, high-context data with reliable quality.

You will collaborate with engineering, product, and data science teams to deliver production-grade software, ensure low latency, and maintain data freshness across complex data ecosystems

Qualifications

• 6+ years of experience as a Data Engineer or in a closely related technical role.
• Proficiency in data modeling, graphs, and robust ETL/ELT pipelines (Airflow, dbt).
• Experience with graph databases (Neo4j, AWS Neptune).
• Strong Python, SQL, and Spark skills.
• Hands-on cloud experience (AWS, Azure, GCP) and Snowflake.
• Problem-solving and cross-functional collaboration.
• Excellent communication.

Responsibilities

• Design, build, and scale data pipelines and graphs for AI agents.
• Develop identity graphs and real-time data for agentic systems.
• Ensure data quality, latency, and freshness across pipelines.
• Collaborate with engineering, product, and data science teams.
• Lead automation of data delivery and integration with APIs.
• Write production-grade software with secure, optimized code.
• Perform on-call triage of production data issues.

Skills

Python

SQL

Spark

Airflow

dbt

ETL/ELT pipelines

Data graphs

Graph DBs

Cloud platforms

Collaboration

Tools

Snowflake

AWS

Neo4j

AWS Neptune

Google Cloud

dbt

Job description

Salesforce seeks a Senior Data Engineer to join the Data & Analytics organization and build scalable data pipelines and graphs powering its AI-driven agentic customer interactions. You will bridge raw data systems and the agentic layer, grounding AI agents in real-time, high-context data with reliable quality.

You will collaborate with engineering, product, and data science teams to deliver production-grade software, ensure low latency, and maintain data freshness across complex data ecosystems