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.