Associate Distinguished Engineer - Solution Architect

Nagarro; Región Centro; Presencial; MXN 900.000 - 1.300.000; Jornada completa

Descripción de la vacante

Nagarro is seeking a Senior Data/ Solution Architect to define and maintain the KM data platform architecture, spanning ingestion, storage, and security. You will set standards, guide data modeling, and evaluate tools in collaboration with data engineers and product teams.

The role requires 8+ years in data/solution architecture, deep Unity Catalog governance, and experience with AI/LLM-driven consumption patterns. This is a full-time, on-site position in Mexico.

Formación

• 8+ years of experience in data/solution architecture roles, with significant hands-on or architectural experience in Databricks/Lakehouse environments.
• Deep understanding of Unity Catalog governance, data product design, and security classification models.
• Demonstrated experience architecting platforms that handle both structured and unstructured content at scale.
• Experience architecting for AI/LLM-driven consumption patterns (retrieval-augmented generation, vector search, agent-based data access) is highly valued.
• Strong track record of translating business/program roadmaps into technical architecture and staged delivery plans.
• Excellent stakeholder management skills — able to work across engineering, product, legal/privacy, and executive audiences.
• Experience leading architecture reviews and setting technical standards for a growing engineering team.

Responsabilidades

• Define and maintain the overall technical architecture for the KM data platform, spanning ingestion, storage (Databricks/Unity Catalog), transformation, security, and consumption layers.
• Translate multi-year program roadmaps into phased architectural plans, balancing near-term pilot needs against long-term scalability.
• Set architectural standards and guardrails for data modeling, pipeline design, and catalog registration, in partnership with the Senior Data Modeler and Data Engineers.
• Evaluate and recommend platform components, tools, and integration patterns (e.g., Unity Catalog vs. alternative catalogs, orchestration tools, vector search/embedding infrastructure).
• Lead technical design reviews and ensure alignment across data engineering, security/privacy, and downstream product teams (Knowledge Products, Research Products).
• Own non-functional requirements: scalability, performance, security, cost, and reliability of the platform architecture.
• Serve as the primary technical point of contact for architecture workshops and planning sessions (e.g., multi-day cross-functional architecture planning events).
• Assess technical risk and dependencies across workstreams and flag issues to the Engineering Manager and program leadership.
• Stay current on Databricks platform capabilities and enterprise AI/knowledge management architecture trends, bringing recommendations back to the team.

Conocimientos

Databricks

Unity Catalog

Data architecture

AI/LLM patterns

Stakeholder management

Architecture reviews

Security governance

Azure Data Factory

Databricks (Tools)

Herramientas

Azure Data Factory

Databricks

Descripción del empleo

• Full-time
• Service Region: UCC

Company Description

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (15000+ experts across 26 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Job Description

Key Responsibilities

• Define and maintain the overall technical architecture for the KM data platform, spanning ingestion, storage (Databricks/Unity Catalog), transformation, security, and consumption layers.
• Translate multi-year program roadmaps into phased architectural plans, balancing near-term pilot needs against long-term scalability.
• Set architectural standards and guardrails for data modeling, pipeline design, and catalog registration, in partnership with the Senior Data Modeler and Data Engineers.
• Evaluate and recommend platform components, tools, and integration patterns (e.g., Unity Catalog vs. alternative catalogs, orchestration tools, vector search/embedding infrastructure).
• Lead technical design reviews and ensure alignment across data engineering, security/privacy, and downstream product teams (Knowledge Products, Research Products).
• Own non-functional requirements: scalability, performance, security, cost, and reliability of the platform architecture.
• Serve as the primary technical point of contact for architecture workshops and planning sessions (e.g., multi-day cross-functional architecture planning events).
• Assess technical risk and dependencies across workstreams and flag issues to the Engineering Manager and program leadership.
• Stay current on Databricks platform capabilities and enterprise AI/knowledge management architecture trends, bringing recommendations back to the team.

Required Qualifications

• 8+ years of experience in data/solution architecture roles, with significant hands-on or architectural experience in Databricks/Lakehouse environments.
• Deep understanding of Unity Catalog governance, data product design, and security classification models.
• Demonstrated experience architecting platforms that handle both structured and unstructured content at scale.
• Experience architecting for AI/LLM-driven consumption patterns (retrieval-augmented generation, vector search, agent-based data access) is highly valued.
• Strong track record of translating business/program roadmaps into technical architecture and staged delivery plans.
• Excellent stakeholder management skills — able to work across engineering, product, legal/privacy, and executive audiences.
• Experience leading architecture reviews and setting technical standards for a growing engineering team.

Preferred Qualifications

• Experience in professional services, consulting, or other knowledge-intensive industries.
• Familiarity with enterprise search/knowledge platforms (Glean, SharePoint, ServiceNow) and their integration patterns.
• Experience navigating legal/risk/privacy review processes for data platforms.
• Prior experience standing up a data platform team from a nascent or pilot stage to a scaled production capability. Success Metrics (First 6–12 Months)
• Documented target-state architecture for the KM data platform, validated with key stakeholders (Engineering Manager, Data Modeler, Product Owners).
• Architectural standards adopted across data modeling and engineering workstreams.
• Clear, staged technical roadmap aligned to the broader program timeline (e.g., through 2027).

Qualifications

Must have skills: Azure Data Factory, Data Modeling (Strong), Databricks