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Meta · 4 months ago

Data Management Analyst (Short Term Employee)

Menlo Park, CA

Full-time

Onsite

Senior Level

$124K/yr - $176K/yr

5+ years exp

Meta builds technologies that help people connect, find communities, and grow businesses. The Data Management Analyst will be instrumental in building a robust semantic layer for People data, ensuring data quality and security while optimizing data architecture and processes to enable AI-driven insights and analytics.

Computer Software

Comp. & Benefits

Responsibilities

Develop and implement data architecture that complement data engineering design and policies, optimize querying processes to reduce time to insight. This includes designing data models, data warehousing solutions, and data integration frameworks that support the organization's data strategy

Design and develop a holistic metrics aggregation and computation layer across people analytics, enabling the optimization of standard report production, enhancement of dashboard performance, and driving self-service analytics. This involves creating a unified framework for metric calculation, data aggregation, and data visualization

Leverage subject matter expertise and business data process knowledge to design optimal data architecture that meets the needs of stakeholders. This requires a experience understanding of business operations, data flows, and data requirements

Act as a bridge between the Business, People Analytics, and Engineering teams, empowering efficient decision-making by facilitating collaboration, communication, and data-driven insights

Build ontology and AI-consumable data architecture and metadata, enabling the development of artificial intelligence and machine learning solutions. This involves creating data structures, taxonomies, and metadata frameworks that support AI applications

Develop a comprehensive Data Governance framework and artifacts that provide a 360-degree view of a metric, supporting data literacy and catalog development. This includes creating data governance policies, procedures, standards, and guidelines that ensure data quality, security, and compliance

Drive certification of metrics definitions and drive risk management ways of working in People Analytics. Drive Data Quality framework and implement Data Quality rules that is reactive and proactive. Validate data lineage and modernize data governance across People Analytics