Job title: Graph DB Engineer – Sr. Consultant

About

At Deloitte, we do not offer you just a job, but a career in the highly sought-after risk management field. We are one of the business leaders in the risk market. We work with a vision to make the world more prosperous, trustworthy, and safe. Deloitte’s clients, primarily based outside of India, are large, complex organizations that constantly evolve and innovate to build better products and services. In the process, they encounter various risks and the work we do to help them address these risks is increasingly important to their success—and to the strength of the economy and public security.

By joining us, you will get to work with diverse teams of professionals who design, manage, implement & support risk-centric solutions across a variety of domains. In the process, you will gain exposure to the risk-centric challenges faced in today’s world by organizations across a range of industry sectors and become subject matter experts in those areas.

Our Audit & Assurance services professionals help organizations effectively navigate business risks and opportunities—from strategic, reputation, and financial risks to operational, cyber, and regulatory risks—to gain competitive advantage. We apply our experience in ongoing business operations and corporate lifecycle events to help clients become stronger and more resilient. Our market-leading teams help clients embrace complexity to accelerate performance, disrupt through innovation, and lead in their industries. We use cutting-edge technology like AI/ML techniques, analytics, and Robotic Process Automation (RPA) to solve Deloitte’s clients ‘most complex issues. Working in Audit & Assurance at Deloitte US-India offices has the power to redefine your ambitions.

The Team Internal Audit

As part of Digital Internal Audit team, you will be part of our USI Internal Audit practice and will be responsible for scaling digital capabilities for our IA clients. Responsibilities will include helping our clients adopt digital through various stages of their Internal Audit lifecycle, from planning till reporting.

Work you’ll do

The key job responsibilities will be to:

•       Design and implement efficient and scalable graph data models and entity networks using Neo4j

•       Translate business requirements into effective graph schemas and data structures.

•       Develop and maintain graph database instances, including installation, configuration, and performance tuning.

•       Implement data ingestion and transformation pipelines to populate graph databases from various data sources.

•       Develop and optimize Cypher or other graph query languages for complex data retrieval and analysis.

•       Implement data security and access control mechanisms for graph databases.

•       Deploy and operate Milvus (or equivalent vector store) for embedding search and hybrid retrieval

•       Implement embedding ingestion pipelines for similarity and semantic search use cases

•       Design/manage MongoDB repositories supporting upstream/downstream applications

•       Collaborate with data scientists and analysts to develop graph-based analytics solutions.

•       Ensure performance tuning, scalability, availability, and fault tolerance

•       Develop and implement algorithms for graph traversals, community detection, and other graph analytics tasks.

•       Implement data quality checks, monitoring, and error handling

•       Establish and enforce best practices for graph database development and management.

Required skills

•       Strong understanding of graph theory concepts including nodes, edges, properties, traversals, and relationship patterns essential for effective graph database design

•       Demonstrated expertise in one or more graph query languages such as Cypher (Neo4j) for complex data retrieval and manipulation

•       Experience translating business requirements into optimized graph schemas, including property graphs, RDF triples, or knowledge graph ontologies

•       Experience designing, deploying, and administering production graph database systems with consideration for scalability, availability, and security requirements

•       Familiarity with ETL processes, API integrations, or data ingestion frameworks

•       Knowledge of cloud services (AWS, Azure, GCP) and managed graph database offerings

•       Familiarity with Gen AI application design and architecture

•       Demonstrated knowledge of Retrieval-Augmented Generation (RAG) patterns and architectures (e.g., chunking, embeddings, reranking, grounding, and evaluation) to build reliable LLM applications.

•       Design and implement GraphRAG (graph + vector) retrieval pipelines and optimize hybrid retrieval relevance and latency.

•       Expertise in handling large multi-modal data sets and applying data preprocessing techniques to ensure data quality and relevance.

•       Ability to analyze and interpret complex data to derive actionable insights and drive decision-making processes

•       Strong knowledge of programming languages like Python and SQL

•       Familiar with AI/Gen AI Ethics & Governance frameworks, applications and archetypes

Preferred skills

•       Certification in Cloud (AWS/ Azure / GCP)

•       Certification in AI/ML or Data Analytics

Qualification

•    B.Tech/B.E. and/or MBA