Lead Agentic Data Systems Engineer

Salesforce
Mexico City
Workplace: HybridFull timeFunction: IT Operations (Systems/Network Admin)Experience: 5+ yearsSkills: ["Analytical judgment","Problem-solving","Governance","Independent ownership"]

Design and build production-grade data products using an agentic approach, turning architectural blueprints into reliable systems end to end. You’ll architect and maintain a private ecosystem of autonomous agents for ETL, synthetic data generation, QA, and predictive modeling, with verification protocols that validate and peer-review outputs. Build MCP servers for secure access to Snowflake, Salesforce, AWS, and internal catalogs, and ensure governance, integrity, and scalability through code-based oversight.

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FursaFursa
Salesforce
Salesforce
2 months ago

Lead Agentic Data Systems Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 15 hours agoStatus: Live
Reposted: similar role first listed 4 months ago

Job Summary

Design and build production-grade data products using an agentic approach, turning architectural blueprints into reliable systems end to end. You’ll architect and maintain a private ecosystem of autonomous agents for ETL, synthetic data generation, QA, and predictive modeling, with verification protocols that validate and peer-review outputs. Build MCP servers for secure access to Snowflake, Salesforce, AWS, and internal catalogs, and ensure governance, integrity, and scalability through code-based oversight.
Location: Mexico City
Workplace: Hybrid
Employment Type: Full time
Job Function: IT Operations (Systems/Network Admin)
Seniority: Mid level

Key Responsibilities

  • •Architect and maintain a private ecosystem of 10+ autonomous agents specialized in ETL, synthetic data generation, automated QA, and predictive modeling.
  • •Design multi-step reasoning architectures and verification protocols so agents autonomously validate and peer-review their outputs.
  • •Transform ambiguous business requirements into production-ready data products independently, building, maintaining, and enhancing them end to end.
  • •Implement governance and oversight for deployed tools using governance as code for data pipelines and agentic development.
  • •Develop and maintain Model Context Protocol (MCP) servers to provide agents with secure, deep-link access to Snowflake, Salesforce, AWS, and internal data catalogs.

Key Requirements

  • •5+ years of experience in high-stakes data engineering, architecture, or data science.
  • •Production-grade proficiency in Python, dbt, Airflow, and advanced SQL (including Apache Spark and Snowflake).
  • •Expertise in agentic AI development, including prompt engineering and agentic frameworks such as LangGraph.
  • •Advanced understanding of data systems concepts including Data Mesh, Data-as-a-Product, Event-Driven Architectures, semantic layers, and knowledge graphs.
  • •Ability to function as a "Domain Data Officer" with minimal supervision, translating ambiguous requirements into production-ready data products.
Experience:5+ yearsData engineeringData architectureData scienceAI agents
Skills:Analytical judgmentProblem-solvingGovernanceIndependent ownership
Tech Stack:PythonDbtAirflowSQLApache SparkSnowflakeCursorCodexClaude CodeLangGraphPrompt EngineeringMCP serversModel Context ProtocolDockerKubernetesServerlessData MeshData-as-a-ProductEvent-Driven ArchitecturesSemantic layer

Company Brief

Salesforce
Provides a leading cloud-based customer relationship management (CRM) platform with sales, service, marketing, analytics, and integration tools that empower businesses to manage customer relationships and digital transformation at scale.
Industry: SaaS
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Francisco, United States
Founded: 1999
Glassdoor
Glassdoor: 4.1
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