Head of Network Data Platform & AI-Ready Engineering

Unavailable; Quilmes; Remote; ARS 278,173,000 - 432,713,000; Full time

Job summary

Global Network Services seeks an Executive Director, Data Engineering to lead its Network Data engineering org and act as the Argentina IP Foundational Services site lead. You will own the data platform from sourcing to serving, partnering across SRE, automation, and product teams to enable AI-ready, governed data at scale.

You will drive data strategy, establish SLOs, define data contracts, and mentor a global team of engineers, ensuring production-grade, observable pipelines and strong

Qualifications

• 10+ years in data engineering or data platform engineering, including leadership roles running data systems at scale
• Proven ownership of a production data platform with pipelines, modelling, storage, and serving
• Experience establishing data governance with ownership models, data contracts, data quality metrics, lineage, and schema evolution
• Strong hands-on engineering foundation (Python, SQL, APIs, streaming and batch pipelines, modern data stores)
• Proven track record adopting agentic AI and LLM-driven capabilities in production environments
• Experience operating within formal risk and control frameworks: audit engagement, evidence quality standards, remediation governance
• Proven ability to scale teams and drive adoption of common data standards
• Strong global collaboration skills across distributed, matrixed organizations
• Prior site/country/regional engineering hub leadership experience
• BS/BA degree or equivalent practical experience in technology or related field

Responsibilities

• Define and execute the network data strategy including data modelling, sources, distribution, and accessibility for consuming platforms
• Build and operate the data platform with ingestion/streaming pipelines, transformation, storage, modelling, and serving APIs
• Establish consistent data models and identity standards for network entities to enable reliable joins across systems
• Drive data quality as an engineering discipline with validation, testing, monitoring, and quality targets
• Establish data contracts and data SLOs with ownership, versioning and schema evolution
• Implement lineage and observability across data pipelines to trace issues and assess impact
• Collaborate with data governance programs to meet audit, risk, and regulatory obligations
• Make network data AI-ready for agentic and LLM-driven capabilities within the data lifecycle
• Establish engineering standards, testing frameworks, and CI/CD pipelines for production-grade, secure, observable data services
• Deliver measurable outcomes: data SLO attainment, improved quality metrics, faster access, and analytics gains
• Regional responsibilities: Represent Argentina hub in global forums, drive site culture, cross-functional collaboration
• Hire, develop, and retain engineering talent across the Argentina footprint
• Ensure governance, risk, and audit compliance for in-country operations
• Own the data platform and data quality outcomes; scale teams and drive common data standards
• Adopt a product-led approach to data with clear ownership and customer-focused governance
• Communicate with executives to build business cases for foundational data investments
• Maintain compliance and control discipline
• Demonstrate senior regional tech presence to stakeholders and regulators

Skills

Python

SQL

APIs

Streaming pipelines

Batch pipelines

Data modelling

Data governance

LLM adoption

Leadership

Education

BS/BA degree in technology or related field

Job description

Global Network Services seeks an Executive Director, Data Engineering to lead its Network Data engineering org and act as the Argentina IP Foundational Services site lead. You will own the data platform from sourcing to serving, partnering across SRE, automation, and product teams to enable AI-ready, governed data at scale.

You will drive data strategy, establish SLOs, define data contracts, and mentor a global team of engineers, ensuring production-grade, observable pipelines and strong