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Graph Database Engineer
Company: ARA Resources Pvt. Ltd.
Job Location: Bengaluru, Karnataka, India
Employment Type: Full-time
Experience Required: 5 - 10 years
Salary: 25L35L a year
Job Title : Graph Database Engineer
Location : Bangalore
Work Type : Hybrid
Experience - 5-10 Years
Notice Period - 60 Days
About ARA's Client Leading Technology Consulting Firm
ARA's Client is a prominent technology consulting firm known for their innovative solutions and commitment to excellence. They specialize in transforming businesses through advanced technology and data-driven insights. The organization fosters a collaborative culture that encourages continuous learning and professional growth.
Role Summary
As a Data Platform Engineer, the ideal candidate will assist in designing and implementing data platform solutions. They will collaborate with architects to ensure seamless integration and enhance the overall data architecture strategy.
Key Responsibilities
Design scalable, high-performance enterprise graph data solutions.
Architect and design scalable data pipelines for graph data processing.
Devise Labeled Property and Ontology graph models aligned with business use cases.
Create Graph Solution deliverables and obtain necessary sign-offs.
Collaborate with Integration and Data Architects for cohesive system integration.
Engage in discussions to refine data architecture strategies.
Ensure all data platform components support organizational objectives.
Participate in the entire data platform lifecycle.
Must-Have Qualifications
5+ years of overall IT experience.3+ years of experience in Graph-based solutions.
Deep hand-on knowledge in graph databases such as Neo4j, TigerGraph, AWS Neptune, or similar.
Strong proficiency in graph modeling, graph integration and graph query optimization.
Experience in building scalable ETL pipelines.
Work Experience on data transformation and analytic projects.
Experience in at least one programming languages e.g. Python, Scala, SQL.
Nice to Have
Any of these add-on skills - Graph Database Modelling, Ontology, Semantic Data Modeling.
-Familiarity with graph analytics, graph embeddings, or machine learning on graphs.
Preferred understanding of Data Analytics on Cloud landscape and Data Lake knowledge.
Cloud Data Engineering, Cloud Data IntegrationMust be familiar with Data Architecture Principles. .