3 months ago

Principal 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 design and governance of an autonomous, agent-led data platform, acting as a single masterminded engineer who orchestrates a team of AI agents to perform ETL, QA, governance and analytics Workflows, with emphasis on data mesh/DaaP and AI-driven automation.

Location: Mexico City

Workplace: Hybrid

Employment Type: Full time

Job Function: IT Operations (Systems/Network Admin)

Seniority: Manager level

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. Context aware Agent 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

•7+ years of experience in high-stakes Data Engineering, Architecture, or Data Science
•Senior experience with Python & SQL
•Operational leverage: proven history of using generative AI to accelerate output
•Strategic autonomy: ability to function as a Domain Data Officer with minimal supervision
•Technical intuition: strong ability to identify subtle logic errors or hallucinations in agentic output

Experience:7+ yearsData engineeringData architectureData scienceAI automationEnterprise data

Skills:Problem-solvingCommunicationLeadership

Tech Stack:PythonSQLDbtAirflowApache SparkSnowflakeDockerKubernetes

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

3 months ago

Principal 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)

Seniority: Manager level

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. Context aware Agent 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

•7+ years of experience in high-stakes Data Engineering, Architecture, or Data Science
•Senior experience with Python & SQL
•Operational leverage: proven history of using generative AI to accelerate output
•Strategic autonomy: ability to function as a Domain Data Officer with minimal supervision
•Technical intuition: strong ability to identify subtle logic errors or hallucinations in agentic output

Experience:7+ yearsData engineeringData architectureData scienceAI automationEnterprise data

Skills:Problem-solvingCommunicationLeadership

Tech Stack:PythonSQLDbtAirflowApache SparkSnowflakeDockerKubernetes

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