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Salesforce

Builds cloud software for customer relationships

Senior Data Engineer - AI & Data

Data EngineeringConfirmed live in the last 24 hours
Full-timeMexico City, CDMX, MexicoNo salary listed

About the Job

Requirements

  • The candidate must have 5–7 years of hands-on data engineering experience.
  • The candidate must have strong data modeling skills in dimensional, star, and snowflake models, and data curation experience.
  • The candidate must have production experience with dbt and Snowflake, plus working knowledge of Informatica and Airflow.
  • The candidate must have proven use of AI coding assistants and generative AI to deliver measurably faster, with examples.
  • The candidate must have hands-on context engineering and agent design experience, including tool use, reasoning, and self-correction.
  • The candidate must exercise sound judgment to catch logic errors and hallucinations in AI-generated output before production.
  • The candidate must have strong problem-solving skills, attention to detail, and cross-functional communication skills.

Responsibilities

  • Design, build, and maintain automated pipelines and dimensional, star, and snowflake models using dbt, Snowflake, Informatica, and Airflow to power analytics, reporting, and machine learning and artificial intelligence use cases.
  • Integrate data from multiple systems, including Salesforce Core and Data 360, into unified, high-quality datasets.
  • Ensure data accuracy, completeness, and consistency through validation, observability, and automated monitoring; troubleshoot issues and optimize 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 such as Cursor, Codex, and Claude Code to accelerate development, testing, documentation, and troubleshooting.
  • Build agentic workflows for ETL, automated quality assurance, anomaly detection, and pipeline remediation, with agents proposing fixes for review and approval.
  • Design verification patterns, including self-correction loops, peer-review agents, and human-in-the-loop checkpoints, to validate agent output before production.
  • Develop MCP servers that provide 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.
  • Apply governance as code to pipelines and agents, including lineage, access controls, semantic definitions, and audit logging.
  • Support data quality and governance initiatives in line with standards and best practices.
  • Contribute to red-team and validation agents that probe pipelines and agents for logic flaws, vulnerabilities, and integrity risks.
  • Lead and mentor peers on AI-assisted engineering practices.
  • Improve tools, standards, and documentation, and evaluate emerging data and AI technologies with sound judgment.

Desired Qualifications

  • Experience with agentic frameworks and building or consuming MCP servers.
  • Knowledge of Salesforce Core and Data 360.
  • Knowledge of Data Mesh, Data-as-a-Product, event-driven architecture, semantic layers, and knowledge graphs.
  • Experience with AI evaluation, guardrails, and adversarial testing of agents.
  • Statistical and simulation literacy, and experience orchestrating long-running agent workloads.

About the Company

Salesforce

Builds cloud software for customer relationships

Salesforce sells cloud software that helps businesses manage sales leads, customer service, marketing, and online commerce from shared customer records. Its flagship Sales Cloud tracks accounts and deals, while Service Cloud organizes support cases and Agentforce builds AI assistants that act on company data. Teams access these tools through a browser and connect outside apps and data sources, with Slack for work messages and Tableau for visual analysis. Salesforce earns most of its revenue from software subscriptions and support, with professional services for implementation and training. Marc Benioff co-founded Salesforce in 1999, and its headquarters are in San Francisco, California.

Company size
10,001+
Company stage
IPO
Headquarters
San Francisco, CA
Founded
1999

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