Quantexa Data Engineer - Part-Time

Job Summary

We are seeking an experienced Quantexa Data Engineer to design, develop, and support enterprise-scale data engineering solutions using the Quantexa platform. The ideal candidate will have strong expertise in Quantexa, Scala, Apache Spark, and big data technologies.

Key Responsibilities

• Design, develop, and implement data engineering solutions using the Quantexa platform.
• Build, optimize, and maintain scalable data ingestion, ETL, and data processing pipelines.
• Configure Quantexa entity resolution, graph analytics, scoring models, contextual analytics, and risk detection frameworks.
• Develop and maintain high-performance data pipelines using Scala, Apache Spark, SQL, and distributed data processing technologies.
• Integrate Quantexa with enterprise systems, APIs, data lakes, cloud platforms, and downstream applications.
• Perform data modelling, data transformation, data quality validation, and performance optimization.
• Support end-to-end implementation, testing, deployment, and production support activities.
• Troubleshoot production issues, perform root cause analysis, and implement performance improvements.
• Collaborate with business stakeholders, solution architects, and cross-functional teams to translate business requirements into scalable technical solutions.
• Participate in Agile ceremonies, code reviews, CI/CD processes, and DevOps best practices.
• Prepare technical documentation, solution design documents, deployment guides, and operational runbooks.

Requirements

• At least 2 years of experience in Data Engineering, Big Data Engineering,or related fields
• Hands-on experience implementing Quantexa solutions in enterprise environments.
• Strong programming skills in Scala (preferred), Java, or Python.
• Strong experience with Apache Spark, Hadoop, SQL, and distributed data processing.
• Good understanding of Quantexa Entity Resolution, Network Generation, Context Configuration, and Scoring Frameworks.
• Experience developing large-scale ETL/data integration pipelines.
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with Elasticsearch, Parquet, or other big data technologies is advantageous.
• Familiarity with Git, Jenkins, Gradle, Docker, CI/CD pipelines, and DevOps practices.
• Strong analytical, troubleshooting, and problem-solving skills.
• Experience working in Agile/Scrum delivery environments.
• Quantexa certification is highly desirable.
• Domain knowledge in Financial Crime, AML, KYC, Fraud Detection, Banking, or Risk Management is preferred.