Data engineer (Quantexa)

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 the health, availability, and performance of the data infrastructure

Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference

Requirements

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.