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COE Leader – Graph Data Engineering

Chennai, Bangalore, Hyderabad
Job Description
Who we are

Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty andmove forward decisively. Our purpose is to provide certainty to shape a better tomorrow.
Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of our team leaders rank in Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence.
We are a Great Place to Work-Certified™ (2022-24), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and others. We have been ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine. Curious about the role? What your typical day would look like?

About the Role
We are looking for an accomplished COE Leader – Graph Data Engineering (Sr. Solutions Architect) to lead our efforts in building solutions, capabilities, and go-to-market strategies in the Graph Data Engineering + GenAI space. This role combines hands-on solution architecture expertise with practice leadership responsibilities, driving innovation and growth in areas such as Graph Databases, Knowledge Graphs, Databricks, and Large Language Models (LLMs)/Generative AI.
The ideal candidate will be a strong engineering technologist and thought leader who can incubate a COE, mentor teams, and partner with clients to deliver differentiated solutions.

Key Responsibilities:-
Solution Architecture and Delivery

  • Provide SME & architecture guidance to various teams on various Graph-based project
  • Lead the design of enterprise-grade solutions leveraging Graph Databases, Databricks, and Gen AI.
  • Drive integration of LLMs/GenAI with graph-powered data and analytics solutions (e.g., RAG, semantic search, enterprise knowledge assistants).
  • Serve as the technical partner for clients, engaging in architecture discussions, solution reviews, and delivery governance.
  • Ensure best practices, scalability, and performance across implementations. COE Leadership & 

Capability Building

  • Engage as an SME in our various Graph Data Engineering projects.
  • Establish and lead the Graph Data Engineering COE, including defining vision, roadmap, and operating model.
  • Build reusable accelerators, frameworks, and solution blueprints for graph-powered AI solutions.
  • Mentor and upskill internal teams to strengthen expertise in graph technologies and knowledge engineering.
  • Evaluate and onboard emerging graph/AI technologies to stay ahead of the curve.

Go-To-Market & Growth Enablement

  • Partner with sales and presales teams to develop GTM offerings, proposals, and client solutioning.
  • Engage directly with clients during discovery workshops, RFPs, and strategy sessions.
  • Represent the COE in industry forums, thought leadership content, and strategic alliances with partners (e.g., Neo4j, and various cloud providers).
  • Drive pipeline growth by evangelizing graph + AI solutions across accounts and industries.

Job Requirement
Required Skills and Experience

  • 12–15 years of overall experience in Data Engineering, Advanced Analytics, or AI/ML solutions.
  • Proven expertise with Graph Databases (Neo4j, AWS Neptune, Stardog, Timbr, etc.) and Knowledge Graphs.
  • Strong Graph Data modeling skills.
  • Hands-on experience with Databricks (PySpark, Delta Lake, Data Lakehouse, Unity Catalog) and cloud-native data platforms (Azure/AWS/GCP).
  • Practical experience in designing and delivering LLM/GenAI-enabled solutions with knowledge graphs and vector search.
  • Track record in solutioning, presales, and GTM enablement, including RFPs and client engagement.
  • Demonstrated experience in practice/COE building, capability incubation, and team mentoring.
  • Excellent communication, storytelling, and client-facing skills.

Good-to-Have Skills

  • Experience with vector databases (Pinecone, etc.) and NLP & embeddings pipelines.
  • Knowledge of ontologies, taxonomies, and semantic modeling.
  • Exposure to building AI-powered knowledge assistants, RAG-based enterprise solutions, or domain-specific knowledge platforms.