Senior Analytics Architect: AI-Ready Data Foundations

LinkedIn; New York (NY); Hybrid; USD 148,000 - 243,000; Full time

Job summary

LinkedIn is hiring a Sr. Staff Analytics Architect to define the target-state architecture for People Analytics data products, governance, and AI-enabled capabilities.

You will lead across analytics engineering, governance, and reporting platforms to establish standards used by multiple teams. The role is hybrid, based in multiple US cities, and requires extensive experience in data architecture, governance, and scalable data platforms.

Qualifications

• Bachelor's degree in a related technical field or equivalent practical experience.
• 12+ years of experience in data architecture, analytics architecture, data engineering, data platforms, or related technical disciplines.
• Experience architecting enterprise-scale data ecosystems from source systems through analytics, reporting, and downstream consumption layers.
• Experience with cloud-based data platforms, lakehouse architectures, and modern analytics ecosystems.
• Strong experience with data modeling, including dimensional, relational, semantic, canonical, and master data models.
• Experience developing architecture standards, governance frameworks, and scalable data platform solutions.
• Experience partnering with engineering, analytics, product, governance, and business stakeholders.
• Experience evaluating technical trade-offs and communicating recommendations to both technical and non-technical audiences.

Responsibilities

• Define target-state architecture for enterprise People Analytics platforms, including data products, semantic models, APIs, BI solutions, and AI-enabled capabilities.
• Design and maintain certified metric frameworks, dimensional models, semantic models, conformed dimensions, calculation standards, data certification processes, and governance controls.
• Establish architecture patterns enabling scalable consumption of people data through analytics platforms, self-service reporting, APIs, ML models, and AI applications.
• Create technical specifications, logical data models, source-to-target mappings, reference architectures, integration patterns, security frameworks, and implementation standards.
• Partner with engineering, governance, analytics, and business stakeholders to translate data architecture requirements into scalable technical solutions.
• Define architecture standards for metadata management, data lineage, data quality, observability, master data management, access controls, and auditability.
• Establish approaches for statistical, predictive, and ML outputs, including governance, model lifecycle, output management, and responsible AI practices.
• Design AI-ready data foundations, including knowledge management frameworks, retrieval architectures, metadata strategies, and governance patterns.
• Lead architecture reviews, evaluate technology options, document decisions and trade-offs, and drive alignment across teams.
• Develop reusable standards, blueprints, and best practices that improve consistency, scalability, and long-term platform sustainability.
• Influence technical strategy and architectural direction across multiple teams without direct management.
• Partner with senior leaders to align investments with business objectives and evolving analytics priorities.

Skills

Data architecture

Analytics architecture

Data engineering

Cloud data platforms

Data modeling

Governance frameworks

Stakeholder collaboration

Communication of trade-offs

Education

Bachelor's degree or equivalent practical experience

Tools

Databricks

Unity Catalog

Power BI

Visier

Job description

LinkedIn is hiring a Sr. Staff Analytics Architect to define the target-state architecture for People Analytics data products, governance, and AI-enabled capabilities.

You will lead across analytics engineering, governance, and reporting platforms to establish standards used by multiple teams. The role is hybrid, based in multiple US cities, and requires extensive experience in data architecture, governance, and scalable data platforms.