

Data Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer (GCP) with a 6-month contract, remote in the UK. Requires 5+ years of data engineering experience, 2+ years with Neo4j, proficiency in SQL and GCP services, and a Google Professional Data Engineer certification.
π - Country
United Kingdom
π± - Currency
Β£ GBP
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π° - Day rate
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ποΈ - Date discovered
July 5, 2025
π - Project duration
More than 6 months
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ποΈ - Location type
Remote
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
United Kingdom
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π§ - Skills detailed
#Data Security #Kafka (Apache Kafka) #Metadata #Python #SQL (Structured Query Language) #IAM (Identity and Access Management) #GIT #AWS (Amazon Web Services) #Version Control #Databases #Security #Apache Beam #Knowledge Graph #Graph Databases #Data Management #Apache Spark #Data Science #Programming #Storage #Libraries #Data Pipeline #Dataflow #Schema Design #Scripting #Data Engineering #Data Architecture #Spark (Apache Spark) #"ETL (Extract #Transform #Load)" #Cloud #Data Ingestion #Data Manipulation #Airflow #Apache Airflow #BigQuery #Compliance #Data Governance #Neo4J #Data Catalog #Datasets #Scala #Big Data #Clustering #Data Lake #Data Processing #Java #GDPR (General Data Protection Regulation) #Hadoop #Azure #GCP (Google Cloud Platform) #Computer Science
Role description
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Job Title: Data Engineer - GCP
Location: UK - Remote
Duration: 6 Months (extendable)
Employment Type: Contract B2B
Roles & Responsibilities:
About the Role
We are seeking a highly skilled Data Engineer with hands-on experience in Graph Databases (Neo4j) and modern data ingestion and optimization techniques. You will help EMEA clients design intelligent data platforms leveraging GCP services to support complex, connected data use cases and drive performance at scale.
Key Responsibilities
β’ - Architect and build data pipelines on GCP integrating structured, semi-structured, and unstructured data sources.
β’ - Design, implement, and optimize Graph Database solutions using Neo4j, Cypher queries, and GCP integrations.
β’ - Develop ETL/ELT workflows using Dataflow, Pub/Sub, BigQuery, and Cloud Storage.
β’ - Design graph models for real-world applications such as fraud detection, network analysis, and knowledge graphs.
β’ - Optimize performance of graph queries and design for scalability.
β’ - Support ingestion of large-scale datasets using Apache Beam, Spark, or Kafka into GCP environments.
β’ - Implement metadata management, security, and data governance using Data Catalog and IAM.
β’ - Work across functional teams and clients in diverse EMEA time zones and project settings.
Required Qualifications
β’ Bachelor's degree in Computer Science, Engineering, or a related field.
β’ 5+ years of experience in data engineering, including 2+ years with Neo4j or another Graph DB platform.
β’ 4+ years of hands-on experience as a Data Engineer, with at least 2+ years specifically working with Google Cloud Platform (GCP) data services.
β’ Strong proficiency in SQL and experience with schema design and query optimization for large datasets.
β’ Expertise in BigQuery, including advanced SQL, partitioning, clustering, and performance tuning.
β’ Hands-on experience with at least one of the following GCP data processing services: Dataflow (Apache Beam), Dataproc (Apache Spark/Hadoop), or Composer (Apache Airflow).
β’ Proficiency in at least one scripting/programming language (e.g., Python, Java, Scala) for data manipulation and pipeline development.
β’ Understanding of data warehousing and data lake concepts and best practices.
β’ Experience with version control systems (e.g., Git).
β’ - Proficiency in SQL, Python, and Cypher query language.
β’ - Strong hands-on experience with BigQuery, Dataflow, Pub/Sub, and Cloud Storage.
β’ - Knowledge of graph theory, graph schema modeling, and data relationship mapping.
β’ - Fluent in English.
β’ - Certification: Google Professional Data Engineer or equivalent (e.g., AWS Big Data, Azure Data Engineer).
Preferred Qualifications
β’ - Overall 8 to 10+ years of experience
β’ - Experience in creating open-source Graph DB (Neo4j), data ingestion and optimization techniques
β’ - Familiarity with Graph Data Science libraries in Neo4j.
β’ - Understanding of data architecture principles, data mesh, and distributed processing.
β’ - Prior experience in customer-facing roles or professional services.
β’ - Background in data security, compliance (e.g., GDPR), and regional data residency awareness.