Role Summary
We are seeking a
Lead, GenAI Database Engineer
to design, build, and scale next-generation
AI-native data platforms
that power Generative AI, Retrieval-Augmented Generation (RAG), and Knowledge Graph–driven applications. This role sits at the intersection of
graph theory, vector search, relational data modeling, and AI systems
, with a strong emphasis on
hands-on technical leadership
.
You will be responsible for architecting and implementing
multi-modal data ecosystems
that combine
Graph Databases, Vector Databases, and Relational Databases
to enable explainable, scalable, and production-grade GenAI solutions.
Key Responsibilities
1. GenAI Data Architecture & Platform Design
Design and lead
end-to-end GenAI data architectures
supporting:
Retrieval-Augmented Generation (RAG)
Knowledge Graph–augmented LLMs (good to have)
Hybrid semantic + symbolic reasoning systems
Architect
polyglot persistence strategies
, determining where Graph, Vector, and Relational databases are used and how they interoperate.
Establish data standards, schemas, indexing strategies, and performance benchmarks for AI-driven workloads.
2. Graph Database & Knowledge Graph (Hands-on)
Own the
design, development, and optimization of Knowledge Graphs
for enterprise-scale use cases.
Model complex domains using
nodes, edges, properties, and ontologies
.
Implement advanced graph capabilities:
Entity resolution and linking
Schema and ontology design (RDF / OWL where applicable)
Graph inference, traversal, and reasoning
Hands-on experience with
graph query languages
.
Engineer performant graph pipelines using databases.
3. Vector Databases & Semantic Retrieval
Lead the implementation of
vector-based retrieval systems
to support semantic search and RAG pipelines.
Design and manage:
Embedding storage and lifecycle management
Chunking, indexing, and hybrid retrieval strategies
Optimize vector similarity search for scale, latency, and relevance.
4. Relational Database & Enterprise Data Engineering
Design and maintain
high-performance relational schemas
supporting transactional, analytical, and AI workloads.
Leverage RDBMS platforms such as:
PostgreSQL
MySQL
SQL Server
Oracle
Implement:
Advanced indexing strategies
Query optimization
Stored procedures and data integrity constraints
Ensure smooth integration between relational systems and Graph/Vector layers.
5
.
Technical Leadership & Governance
Act as a
technical lead and mentor
for database and GenAI engineers.
Review architecture designs, code, and data models.
Establish best practices for:
AI data governance
Security, privacy, and compliance
Metadata management and lineage
Partner with product, ML, and business stakeholders to translate use cases into scalable data solutions.
Required Qualifications
Core Technical Skills
Expert-level hands-on experience
with:
Graph Databases
Vector Databases
Relational Databases
Good to have experience in designing and implementing
Knowledge Graphs
in production.
Deep understanding of:
Graph theory and graph algorithms
Vector similarity search and embeddings
SQL and relational modeling
Leadership Competencies
Strong system-level thinking across data, AI, and infrastructure.
Ability to influence architecture decisions across teams.
Excellent communication skills with both technical and non-technical stakeholders.
Bias toward ownership, hands-on execution, and continuous improvement.
5+ years overall experience
in advanced data platforms
and
3+ years in GenAI / Graph database–driven systems
Our Benefits
Flexible working environment
Volunteer time off
LinkedIn Learning
Employee-Assistance-Program (EAP)
NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://www.nielseniq.com/global/en/ai-safety-policies.
About NIQ
NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.
For more information, visit NIQ.com
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Our commitment to Diversity, Equity, and Inclusion
At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the
https://nielseniq.com/global/en/news-center/diversity-inclusion
