GenAI Engineer - Database at NielsenIQ

Pune City, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

15 Jul, 26

Salary

0.0

Posted On

16 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Graph Databases, Vector Databases, Relational Databases, Generative AI, RAG, Knowledge Graphs, Data Architecture, SQL, PostgreSQL, MySQL, Data Modeling, System Design, Technical Leadership, Semantic Search, Embedding Management, Graph Algorithms

Industry

Software Development

Description

Job Description 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. Qualifications 5+ years overall experience in advanced data platforms and 3+ years in GenAI / Graph database–driven systems Additional Information 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 Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook 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

Responsibilities

Design and lead end-to-end GenAI data architectures that integrate graph, vector, and relational databases for scalable AI applications. Provide technical leadership and governance while mentoring engineers to ensure high-performance data solutions.