Quantexa Data Engineer (Spark ,Scala, Elastic Search) job opportunity at Unison Group.



Date2026-02-03T04:08:57.589Z bot
Unison Group Quantexa Data Engineer (Spark ,Scala, Elastic Search)
Experience: 5-years
Pattern: Full-time
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Scala, Elastic Search)

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loacation Singapore, Singapore
loacation Singapore....Singapore

We are seeking a talented and experienced Data Engineer (Quantexa)with expertise in Hadoop, Scala, Spark, Elastic, Open Shift Container Platform (OCP) and DevOps practices. Elasticsearch 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 tool 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 the health, availability, and performance of the data infrastructure ·        Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference More than 5 years of experience as a Data Engineer · Bachelor's or Master's degree in Computer Science, Software Engineering, or a related discipline · Possession of Quantexa certification as a Data Engineer or Data Architec t, with proficiency in the tool · Demonstrated experience as a Data Engineer, utilizing Hadoop, Spark, and data processing technologies in large-scale environments · Expertise in the Scala programming language and familiarity with functional programming principles · Prior experience with the Quantexa tool is highly desirable · Comprehensive understanding of Apache Spark architecture, including RDDs, DataFrames, and Spark SQL · Advanced proficiency in designing and developing data infrastructure utilizing Hadoop, Spark, and associated tools (HDFS, Hive, Pig, etc.) · Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration via Kubernetes · Proficiency in programming languages commonly employed in data engineering, including Spark, Python, Scala, or Java · Knowledge of DevOps methodologies, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket) · Experience with Graphana, Prometheus, and Splunk will be considered an added advantage · Background in integrating and utilizing Elasticsearch for data indexing and search applications · Solid understanding of Elasticsearch data modeling, indexing strategies, and query optimization techniques · Experience with distributed computing, parallel processing, and handling large datasets · Proficient in performance tuning and optimization methods for Spark applications and Elasticsearch queries · Strong problem-solving and analytical capabilities with the capacity to debug and resolve intricate issues · Familiarity with version control systems (e.g., Git) and collaborative development environments

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