Quantexa Data Engineer sn

We are seeking a talented and experienced Data Engineer with expertise in Hadoop, Scala, Spark, Elastic, Open Shift Container Platform (OCP) and DevOps practices to join our team. As a Data Engineer, you will play a crucial role in designing, developing, and optimizing big data solutions using Apache Spark, Scala, and Elasticsearch. You will collaborate with cross-functional teams to build scalable and efficient data processing pipelines and search applications. Knowledge and experience in the Compliance / AML domain will be a plus. Working experience with Quantexa software is a must. Responsibilities: . Implement data transformation, aggregation, and enrichment processes to support various data analytics and machine learning initiatives . Collaborate with cross-functional teams to understand data requirements and translate them into effective data engineering solutions . Design, develop, and implement Spark Scala applications and data processing pipelines to process large volumes of structured and unstructured data . Integrate Elasticsearch with Spark to enable efficient indexing, querying, and retrieval of data . Optimize and tune Spark jobs for performance and scalability, ensuring efficient data processing and indexing in Elasticsearch . Implement data transformations, aggregations, and computations using Spark RDDs, DataFrames, and Datasets, and integrate them with Elasticsearch . Develop and maintain scalable and fault-tolerant Spark applications, adhering to industry best practices and coding standards . Troubleshoot and resolve issues related to data processing, performance, and data quality in the Spark-Elasticsearch integration . Monitor and analyze job performance metrics, identify bottlenecks, and propose optimizations in both Spark and Elasticsearch components . Ensure data quality and integrity throughout the data processing lifecycle . Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques . Optimize data engineering workflows for containerized deployment and efficient resource utilization . Collaborate with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability . Implement data governance practices, data lineage, and metadata management to ensure data accuracy, traceability, and compliance . Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements . Implement monitoring and logging mechanisms to ensure thehealth, availability, and performance of the data infrastructure . Document data engineering processes, workflows, andinfrastructure configurations for knowledge sharing and reference Education: . Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field . At least 2 years' relevant IT experience, preferably in a Compliance Domain of a Finance Institution.

Essential: . Must be Quantexa certified data engineer / data architect and proficient with the software. . You must be the experienced developer, with good experience in system integration/interfacing. . You will typically be assigned to work on specific projects and is expected to support the Application Delivery Manager (ADM) in all relevant technical matters, end-to-end, within the project. . Depending on the project, your duties may include coding, scripting, building new systems (where necessary) and interfaces. For new system build-up, you may need to environment support during SIT/UAT. . You are expected to ensure your work are adequately documented and transferred to the production team post-cutover. . You will be expected to work with the senior developers and system architect in formulating technical solutions that is fit for purpose for your assigned projects. The solution will need to satisfy all security, regulatory and architectural standards. . Must be Quantexa certified data engineer / data architect andproficient with the software. . Proven experience as a Data Engineer, working with Hadoop,Spark, and data processing technologies in large-scale environments . Proficiency in Scala programming language and familiarity withfunctional programming concepts . Experience with Quantexa tool is highly preferred. . In-depth understanding of Apache Spark architecture, RDDs,DataFrames, and Spark SQL . Strong expertise in designing and developing data infrastructureusing Hadoop, Spark, and related tools (HDFS, Hive, Pig, etc) . Experience with containerization platforms such as OpenShiftContainer Platform (OCP) and container orchestration using Kubernetes . Proficiency in programming languages commonly used in dataengineering, such as Spark, Python, Scala, or Java . Knowledge of DevOps practices, CI/CD pipelines, andinfrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket) . Experience with Graphana, Prometheus, Splunk will be an addedbenefit . Experience integrating and working with Elasticsearch for dataindexing and search applications . Solid understanding of Elasticsearch data modeling, indexingstrategies, and query optimization . Experience with distributed computing, parallel processing, andworking with large datasets . Proficient in performance tuning and optimization techniques forSpark applications and Elasticsearch queries . Strong problem-solving and analytical skills with the ability todebug and resolve complex issues . Familiarity with version control systems (e.g., Git) andcollaborative development workflows . Excellent communication and teamwork skills with the ability towork effectively in cross-functional team Experience with cloud platforms (e.g., AWS,Azure, GCP) and their data services is a plus What you need to do now If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call Shabnam at Hays on +65 60271964 or email (HIDDEN TEXT) for a confidential discussion. Referrals are welcome. Registration ID No. R1873584 | EA License number: 07C3924 | Company Registration No. 200609504D