Data Engineer Senior | AI & Data

About the role

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Job Category Software Engineering

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

Senior Data Engineer | AI & Data

DET TEAM

Mexico City

We are seeking a Senior Data Engineer to design, build, and optimize scalable data pipelines and models that power analytics, AI, and business insights. You will work across modern data platforms such as dbt, Snowflake, Informatica, Airflow. You will also use AI-native development tools and agentic workflows to build faster, validate more rigorously, and keep data products reliable.

Key Responsibilities

Data and AI engineering

- Design, build, and maintain automated pipelines and dimensional/star/snowflake models using dbt, Snowflake, Informatica, and Airflow. These power analytics, reporting, and ML/AI use cases.

- Integrate data from multiple systems, including Salesforce Core and Data 360, into unified, high-quality datasets.

- Ensure accuracy, completeness, and consistency through validation, observability, and automated monitoring. Troubleshoot issues and optimize for performance, scalability, and cost.

- Partner with analysts, product managers, and business teams to turn ambiguous requirements into production-ready data products.

- Use AI-native tools (e.g., Cursor, Codex, Claude Code) to accelerate development, testing, documentation, and troubleshooting.

- Build agentic workflows for ETL, automated QA, anomaly detection, and pipeline remediation. Agents propose fixes, and you review and approve them.

- Design verification patterns (self-correction loops, peer-review agents, human-in-the-loop checkpoints) so agent output is validated before production.

- Develop MCP servers that give agents secure, governed access to Snowflake, Salesforce, and internal data catalogs. Use agents to keep documentation, lineage, and metadata current.

- Supervise long-running agent tasks with checkpoints, cost controls, and audit trails. Contribute to agent-assisted modeling and simulation workflows, reviewing assumptions and uncertainty before decisions are acted on.

Governance, quality, and security