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# Data Engineer

- **Company:** Adecco
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Temporary to permanent
- **Skills:** Amazon Web Services, Microsoft Azure, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Query Languages, Distributed Data Store, Graph Database, Python (Programming Language), Machine Learning, Meta-Data Management, Neo4j, Resource Description Framework (RDF), SPARQL, SQL Databases, Unstructured Data, Information Technology, Graphql, Data Management, Machine Learning Operations, Data Pipelines
- **Published:** June 12, 2026
- **Apply:** https://computerjobs.com/us/en/mob/job/2085757A695BD52E41

## About the Role

* Bachelor's or master's degree in computer science, Data Science, Engineering, or related field.
 * 3+ years of experience in data engineering, with strong exposure to knowledge graph technologies.
 * Strong proficiency in Python and SQL.
 * Experience with graph query languages such as SPARQL and Cypher.
 * Hands-on experience with graph databases and frameworks (Neo4j, GraphQL, RDF, or similar).
 * Experience working with cloud platforms such as AWS and/or Azure.
 * Strong data modelling, analytical, and problem-solving skills.
 * Excellent communication skills with the ability to explain complex technical concepts clearly.
 * Proven ability to work collaboratively in distributed, global teams.

Desirable Skills

 * Experience with large-scale distributed data systems.
 * Familiarity with machine learning pipelines and graph analytics.
 * Understanding of data governance, metadata management, and semantic technologies.
 * Experience working in Agile delivery environments.

## Description

We are seeking a talented and motivated Data Engineer to join a global technology and engineering organisation at the forefront of digital transformation, industrial innovation, and intelligent infrastructure. This is a fully remote 6-month contract role, offering the opportunity to work on cutting-edge data platforms and knowledge graph solutions that support complex, real-world challenges across multiple industries., * Build and optimise ETL/ELT pipelines for knowledge graphs and other data sources.

 * Design and manage graph databases such as Neo4j, AWS Neptune, and ArangoDB.
 * Develop semantic data models using RDF, OWL, and SPARQL.
 * Integrate structured, semi-structured, and unstructured data into knowledge graph systems.
 * Ensure data quality, security, and compliance with governance standards.
 * Collaborate with data scientists and architects to support graph-based analytics and machine learning use cases.
 * Monitor, troubleshoot, and enhance data pipelines for performance and reliability.
 * Contribute to best practices in data engineering, documentation, and data architecture standards.


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