Senior Specialist – Data Engineering (Senior Graph Data Engineer)

Location: Hyderabad / Bengaluru / Noida

Experience: 7–11 Years (Role-specific requirement: 10+ Years)
Employment Type: Permanent
Work Mode: Hybrid – Working from the client location
Openings: 1

About the Role

We are looking for an experienced Senior Graph Data Engineer with strong expertise in Enterprise Graph Data Modeling, Neo4j, ANSI-SQL, Python, and Data Engineering. The role involves designing scalable graph architectures, developing graph-based data platforms, and building enterprise-grade ETL/ELT pipelines. The candidate will contribute to advanced data initiatives involving Knowledge Graphs, AI/ML, Semantic Search, and RAG solutions while collaborating with architects and business stakeholders.

Job Description

The candidate will be responsible for designing and implementing enterprise graph data models, schemas, ontologies, and semantic frameworks using technologies such as Neo4j, Amazon Neptune, and Dydra. The role requires expertise in graph query languages, including Cypher, SPARQL, and Gremlin, along with Python development.

The position involves developing and optimizing ETL/ELT pipelines, integrating data from multiple enterprise sources, and delivering graph, relational, analytical, and Lakehouse data solutions using platforms such as Apache Spark, Databricks, and Airflow.

The candidate will also support enterprise data architecture, data governance, security, and performance optimization while implementing CI/CD pipelines and Infrastructure as Code. The role includes technical leadership, architecture reviews, mentoring, and contributing to AI/ML, knowledge discovery, and recommendation system initiatives.

Key Responsibilities

• Design and implement scalable enterprise graph data models and graph-based architectures.
• Build and maintain graph platforms using Neo4j, Amazon Neptune, Dydra, or equivalent technologies.
• Develop graph schemas, ontologies, semantic models, and metadata frameworks.
• Design and optimize ETL/ELT pipelines for integrating data from diverse enterprise sources.
• Develop graph queries, APIs, and data services using Cypher, SPARQL, Gremlin, and Python.
• Build data products supporting analytics, AI/ML, semantic search, RAG, and knowledge discovery.
• Ensure data quality, governance, security, and performance across graph and analytical platforms.
• Lead architecture discussions, implement DevOps practices, mentor engineering teams, and drive technical excellence.

Required Skills

• Enterprise Graph Data Modeling
• Neo4j / Graph Databases
• ANSI-SQL
• Property Graphs (LPG), RDF, Ontologies, and Semantic Modeling
• Graph Query Languages: Cypher, SPARQL, and Gremlin
• Python Development
• ETL/ELT Development
• Apache Spark, Databricks, and Airflow
• Data Integration and Data Engineering
• Relational, Analytical, and Lakehouse Data Modeling
• Distributed Data Platforms
• DevOps, CI/CD, and Infrastructure as Code
• Enterprise Data Architecture

Preferred / Good to Have

• Databricks Lakehouse Platform, Delta Lake, and Unity Catalog.
• AWS services: S3, Neptune, Glue, Athena, IAM, and Lambda.
• Graph Analytics and Graph Data Science.
• Graph-based Machine Learning and AI Solutions.
• Semantic Search, Knowledge Graphs, and RAG Solutions.
• Recommendation Systems and Recommendation Engines.
• Data Visualization tools: Dash, Shiny, Grafana, Splunk, and Databricks Visualization.
• Semantic Modeling Frameworks and Enterprise Metadata Management.
• Graph Data Science Libraries.

Mandatory Skills

• ANSI-SQL
• Neo4j

Candidate Profile

The ideal candidate should have around 10 years of experience in Data Engineering, Data Architecture, or Graph Technologies, with strong hands-on expertise in enterprise graph modeling, Neo4j, Python, and SQL. A Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline is expected. Candidates should demonstrate technical leadership, architecture design capabilities, and experience delivering scalable enterprise data solutions.

Benefits Package

• Competitive salary and benefits package.
• Opportunities for professional growth and development.
• A collaborative and inclusive work environment.
• The opportunity to work on exciting and challenging projects with leading clients.