Quantexa Data Engineer

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.