Chennai, Tamil Nadu
Job Summary
We are looking for a highly skilled Data Engineer / Graph Data Engineer with expertise in Neo4j, Apache Spark, Airflow, BigQuery, Cypher, and Agentic AI to design, build, and optimize scalable data solutions. The ideal candidate will be responsible for developing graph-based data models, implementing large-scale data processing pipelines, and integrating AI-driven agentic workflows to support advanced analytics and intelligent applications.
Key Responsibilities
Design and implement graph database solutions using Neo4j and develop efficient Cypher queries.Build and optimize scalable ETL/ELT pipelines using Apache Spark and Airflow .Develop and manage enterprise data warehouses and analytics solutions in Google BigQuery .Create graph-based data models to support relationship analytics and knowledge graph initiatives.Integrate Agentic AI frameworks for autonomous decision-making and intelligent workflow orchestration.Monitor, troubleshoot, and optimize data pipelines for performance and reliability.Collaborate with data scientists, AI engineers, and business stakeholders to deliver scalable data solutions.Ensure data quality, governance, security, and compliance standards are maintained.Drive best practices in data engineering, automation, and cloud-native architectures.
Skill Requirements
Strong experience with Neo4j Graph Database and Cypher Query Language .Hands-on expertise in Apache Spark (PySpark) for distributed data processing.Experience developing and scheduling workflows using Apache Airflow .Proficiency in Google BigQuery for large-scale data analytics and warehousing.Experience with Agentic AI , AI orchestration frameworks, and LLM-based solutions.Strong programming skills in Python .Understanding of data architecture, ETL/ELT processes, and cloud platforms.Excellent problem-solving, analytical, and communication skills.
Other Requirements
Knowledge Graphs and Graph Analytics.Generative AI and Large Language Models (LLMs).Vector Databases and Retrieval-Augmented Generation (RAG).Google Cloud Platform (GCP).CI/CD and DevOps practices for Data Engineering
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