Meta is looking to build a robust semantic layer for People data to facilitate seamless access, govern the data ecosystem, ensure data quality, integrity, and security, and drive faster insights and analytics. A key aspect is preparing data for AI applications to enable conversational analytics and AI-driven decision-making.
Requirements
- 5+ years of Advanced SQL, PL/SQL , Relational Database and data modelling
- 5+ Years of Data Architecture and data modelling skills set. Implemented / working knowledge of Kimball STAR Schema / Vault modelling techniques
- 3+ years of Visualization, Business Intelligence tools such as Tableau/Looker/Power BI
- 5+ years of QA / Testing and Data Analysis skills set. Experience to drive what if scenarios and advanced analytical skill set
- 5+ Years of Data Governance implementation experience
- 4+ years of Data Stewardship experience, implementing data quality rules and metadata management
- Knowledge of Semantic layer creation for BI tools
Responsibilities
- Develop and implement data architecture that complement data engineering design and policies, optimize querying processes to reduce time to insight.
- 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.
- Leverage subject matter expertise and business data process knowledge to design optimal data architecture that meets the needs of stakeholders.
- Build ontology and AI-consumable data architecture and metadata, enabling the development of artificial intelligence and machine learning solutions.
- Develop a comprehensive Data Governance framework and artifacts that provide a 360-degree view of a metric, supporting data literacy and catalog development.
- 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.
Other
- Act as a bridge between the Business, People Analytics, and Engineering teams, empowering efficient decision-making by facilitating collaboration, communication, and data-driven insights
- Individual compensation is determined by skills, qualifications, experience, and location.
