Salesforce

2 weeks 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: 20 hours agoStatus: Live

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: 4.1

Website LinkedIn Glassdoor

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Salesforce

2 weeks 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: 20 hours agoStatus: Live

Job Summary

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

Company Brief

Salesforce

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: 4.1

Website LinkedIn Glassdoor