Chief Knowledge Graph Engineer

Data Software Engineering

Location-specific conditions & benefits*

Portugal

We are looking for an innovative and skilled Chief Knowledge Graph Engineer to design, construct, and manage advanced knowledge graph solutions, enabling deeper insights through semantic data engineering and sophisticated data handling techniques.

This position requires a visionary professional with a passion for utilizing graph-based technologies to tackle intricate business challenges.

Responsibilities

Design scalable knowledge graph architectures tailored for data-centric applications
Apply semantic data engineering approaches to integrate, transform, and query extensive datasets
Create data models using RDF, RML, and R2RML to enhance consistency and interoperability
Collaborate with teams to deploy and optimize RDF triple store engines, including AnzoGraph and Amazon Neptune
Ensure effective querying and data manipulation with technologies such as SPARQL, XML, and JSON
Guide and mentor team members to develop competencies in graph-based technologies and methodologies
Identify insights and improvement opportunities through analysis of unstructured datasets
Support cloud-based projects with a strong understanding of the AWS platform and related environments
Partner with interdisciplinary teams to address complex data challenges in agile settings
Optimize data workflows for transformation, metadata management, and processing efficiency
Perform root cause analyses to maintain data integrity and ensure accuracy
Keep updated on advancements in graph databases, semantic web, and data modeling

Requirements

7+ years of experience working in semantic data engineering with tools such as RDF, SPARQL, and XML
Proficiency in Python and SQL for effective data querying, extraction, and transformation
Background in utilizing graph query languages and engines, including Tinkerpop, Gremlin, or SPARQL
Knowledge of graph databases such as AnzoGraph and Amazon Neptune, along with familiarity with additional RDF triple store engines
Understanding of NLP engines or LPG-style knowledge graphs is an advantage but not essential
Capability to navigate AWS platforms, with demonstrated expertise in cloud environments
Strong analytical and technical problem-solving skills, including handling unstructured datasets
Competency in Java programming for data-driven applications is an additional asset
Skills in constructing normalized data models and operationalizing knowledge graphs
Excellent interpersonal and collaborative skills for engaging with cross-functional teams

Nice to have

Familiarity with Tinkerpop and Gremlin for enhancing graph-based implementations
Proficiency in developing LPG engines and leveraging them for advanced analytical tasks
Understanding of data architecture frameworks to integrate knowledge graphs seamlessly on cloud platforms
Background in applying advanced techniques in data modeling and semantic enrichment

Benefits

International projects with top brands
Work with global teams of highly skilled, diverse peers
Healthcare benefits
Employee financial programs
Paid time off and sick leave
Upskilling, reskilling and certification courses
Unlimited access to the LinkedIn Learning library and 22,000+ courses
Global career opportunities
Volunteer and community involvement opportunities
EPAM Employee Groups
Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn