3 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: 23 hours agoStatus: Live

Job Summary

Lead the architectural implementation of production-grade, end-to-end data products in a hybrid, agentic environment. Build and maintain a private ecosystem of autonomous data agents, integrate with Snowflake, Salesforce, and AWS, and ensure governance, scalability, and security while delivering high-quality data solutions.

Location: Mexico City

Workplace: Hybrid

Employment Type: Full time

Job Function: IT Operations (Systems/Network Admin)

Key Responsibilities

•Autonomous Scaling: Architect and maintain a private ecosystem of 10+ autonomous agents specialized in ETL, synthetic data generation, automated QA, and predictive modeling.
•Agentic Orchestration: Design multi-step reasoning architectures and verification protocols to ensure agents autonomously validate and peer-review their own outputs.
•Complex Problem Resolution: Transform high-level, ambiguous business requirements into production-ready data products independently, bypassing the need for mid-level project management.
•Governance & Oversight: Use domain knowledge to ensure deployed tools are well governed. Governance as code for data pipelines and Agentic development.
•Contextual Integration: Develop and maintain Model Context Protocol (MCP) servers to provide agents with secure, deep-link access to Snowflake, Salesforce, AWS, and proprietary internal data catalogs.

Key Requirements

•5+ years of experience in high-stakes Data Engineering, Architecture, or Data Science.
•Strong Python / SQL expertise.
•Operational leverage using generative AI to accelerate output.
•Ability to function as a Domain Data Officer, managing end-to-end data strategy with minimal supervision.
•Superior analytical judgment to identify logic errors or hallucinations in agentic output before production.

Experience:5+ yearsData engineeringAIEnterprise dataData meshSalesforce

Skills:PythonSQLAirflowDbtApache SparkSnowflakeDockerKubernetesServerlessLangGraphClaude CodeCodexCursor

Tech Stack:PythonSQLAirflowDbtSparkSnowflakeDockerKubernetesServerlessLangGraphClaudeCodexCursor

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

Loading job details...

Preparing the role view and application actions.

Salesforce

3 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: 23 hours agoStatus: Live

Job Summary

Location: Mexico City

Workplace: Hybrid

Employment Type: Full time

Job Function: IT Operations (Systems/Network Admin)

Key Responsibilities

•Autonomous Scaling: Architect and maintain a private ecosystem of 10+ autonomous agents specialized in ETL, synthetic data generation, automated QA, and predictive modeling.
•Agentic Orchestration: Design multi-step reasoning architectures and verification protocols to ensure agents autonomously validate and peer-review their own outputs.
•Complex Problem Resolution: Transform high-level, ambiguous business requirements into production-ready data products independently, bypassing the need for mid-level project management.
•Governance & Oversight: Use domain knowledge to ensure deployed tools are well governed. Governance as code for data pipelines and Agentic development.
•Contextual Integration: Develop and maintain Model Context Protocol (MCP) servers to provide agents with secure, deep-link access to Snowflake, Salesforce, AWS, and proprietary internal data catalogs.

Key Requirements

•5+ years of experience in high-stakes Data Engineering, Architecture, or Data Science.
•Strong Python / SQL expertise.
•Operational leverage using generative AI to accelerate output.
•Ability to function as a Domain Data Officer, managing end-to-end data strategy with minimal supervision.
•Superior analytical judgment to identify logic errors or hallucinations in agentic output before production.

Experience:5+ yearsData engineeringAIEnterprise dataData meshSalesforce

Skills:PythonSQLAirflowDbtApache SparkSnowflakeDockerKubernetesServerlessLangGraphClaude CodeCodexCursor

Tech Stack:PythonSQLAirflowDbtSparkSnowflakeDockerKubernetesServerlessLangGraphClaudeCodexCursor

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