Quantexa

Looking for 2.5 years of experience to 8 years.

Willing to relocate to Singapore, Notice Period- 30 days only

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 and proficient 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 with functional 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 infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Pig, etc)

• Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration using Kubernetes

• Proficiency in programming languages commonly used in data engineering, such as Spark, Python, Scala, or Java

• Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)

• Experience with Graphana, Prometheus, Splunk will be an added benefit

• Experience integrating and working with Elasticsearch for data indexing and search applications

• Solid understanding of Elasticsearch data modeling, indexing strategies, and query optimization

• Experience with distributed computing, parallel processing, and working with large datasets

• Proficient in performance tuning and optimization techniques for Spark applications and Elasticsearch queries

• Strong problem-solving and analytical skills with the ability to debug and resolve complex issues

• Familiarity with version control systems (e.g., Git) and collaborative development workflows

• Excellent communication and teamwork skills with the ability to work effectively in cross-functional team

• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services is a plus