Job Title: Data Science Tech Lead
Location: Hybrid (Newark, NJ) / Remote
Duration: 6 months (Possibility of Conversion)
Job Description:
- Lead architecture and development of enterprise data products using Denodvirtualization and semantic modeling.
- Define and govern canonical business models, ontologies, business glossaries, and semantic layers.
- Establish architecture standards, naming conventions, governance frameworks, and development best practices.
- Provide technical leadership tData Engineers, AI Engineers, LLMOps Engineers, and platform teams.
Denod& Data Product:
- Design and implement Virtual Data Products
- Develop complex joins, unions, aggregations, and business transformations across multiple source systems.
- Define reusable semantic-layer patterns that support reporting, analytics, APIs, and AI agents.
- Optimize Denodperformance through caching, query pushdown, aggregation strategies, and virtualization best practices.
Integration & APIs
- Design API-first data product architectures.
- Integrate Denodwith:
- AWS services
- Analytics platforms
- Data Catalogs
- AI platforms
- Enterprise APIs
- Support semantic consumption for AI agents and business applications.
- Integration & APIs
- Design API-first data product architectures.
- Integrate Denodwith:
- AWS services
- Analytics platforms
- Data Catalogs
- AI platforms
- Enterprise APIs
- Support semantic consumption for AI agents and business applications.
Required Qualifications
- 10+ years in Data Engineering, Data Architecture, or Analytics Engineering.
- 5+ years of Denodimplementation experience.
- Experience developing enterprise semantic layers and virtualized data products.
- Strong knowledge of:
- Denodo
- AWS (Lambda, Glue, ETL, APIs)
- Data Modeling
- Ontologies
- Data Governance
- API Design
- Experience with:
- Generative AI
- Agentic AI frameworks
- LLMOps
- Strong stakeholder engagement and consulting skills.
Preferred Qualifications
- Experience designing AI-ready data platforms.
- Knowledge of AI Governance standards.
- Familiarity with Bedrock, OpenAI, Anthropic, Azure OpenAI, or similar platforms.
- Experience implementing enterprise metadata, lineage, and semantic governance frameworks.
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