Data Science Tech Lead

Spectraforce

Newark, NJ, United States

15 days ago

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Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

leoforce.us

Tech stack

Clean Code Principles Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Business Analytics Applications Data Analysis Microsoft Azure Business Software Data Architecture Information Engineering Data Governance Extract Transform Load (ETL)

+9 more

Metadata Repositories Generative AI Data Layers AI Platforms Enterprise Integration Data Management Machine Learning Operations Virtual Agents Api Design

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.

Requirements

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.