Senior Data Engineer (Quantexa)

Role Overview

We are partnering with a leading financial institution on a strategic AML data transformation programme. We are seeking an experienced Senior Data Engineer to design, develop, and maintain scalable big data pipelines supporting mission-critical financial crime analytics and regulatory initiatives. The primary application platform is Quantexa within an enterprise banking environment.

Key Responsibilities

• Design, develop, and maintain large-scale data pipelines using Hadoop and Spark.

• Implement transformation, aggregation, and enrichment processes for AML analytics.

• Deploy and optimize data solutions on OpenShift Container Platform (OCP).

• Collaborate with DevOps teams to implement CI/CD pipelines and automation.

• Ensure data governance, lineage, metadata management, and compliance standards.

• Monitor and optimize performance of distributed data processing systems.

• Implement logging, monitoring, and alerting mechanisms (Grafana, Prometheus, Splunk).

• Provide technical leadership and mentor junior engineers.

• Work closely with cross-functional banking stakeholders to translate business requirements into scalable data solutions.

Key Requirements

• Bachelor's degree in Computer Science, Information Technology, or related field.

• Minimum 6 years of experience in Data Engineering within enterprise environments.

• Strong hands-on expertise in Hadoop ecosystem (HDFS, Hive, Spark, Cloudera).

• Proficiency in Scala, Python, Java, and advanced SQL.

• Experience with OpenShift (OCP) and Kubernetes-based container orchestration.

• Strong knowledge of DevOps practices, CI/CD pipelines, Docker, Jenkins, Ansible.

• Experience with job schedulers such as Control-M.

• Banking or AML domain experience preferred.

• Prior experience implementing or supporting Quantexa platform is highly advantageous.

• Exposure to cloud platforms (AWS, Azure, GCP) is a plus.