Quantexa Data Engineer
Job Summary
We are looking for an experienced
Quantexa Certified Data Engineer / Data Architect
to join our growing data engineering team. The ideal candidate will have strong expertise in
Quantexa, Apache Spark, Scala, Hadoop, Elasticsearch, OpenShift (OCP), and DevOps
technologies. You will be responsible for designing, developing, and optimizing enterprise-scale data processing pipelines while supporting Compliance, AML, and Financial Crime solutions.
This role requires hands-on experience with large-scale distributed systems, data integration, containerized deployments, and CI/CD practices.
Key Responsibilities
Design, develop, and maintain scalable data engineering solutions using Apache Spark, Scala, Hadoop, and Quantexa. Build high-performance data pipelines to process structured and unstructured datasets. Develop Spark applications utilizing RDDs, DataFrames, Datasets, and Spark SQL. Design and implement data transformation, enrichment, aggregation, and validation processes. Integrate Elasticsearch with Spark applications for indexing, search, and analytics. Optimize Spark jobs and Elasticsearch queries for maximum performance and scalability. Develop and maintain robust, fault-tolerant distributed data processing applications. Deploy and manage applications on OpenShift Container Platform (OCP) using Kubernetes. Collaborate with DevOps teams to implement CI/CD pipelines and automate deployments. Support SIT, UAT, deployment activities, and production cutover. Implement monitoring, logging, and performance optimization using industry-standard tools. Ensure data quality, governance, lineage, metadata management, and regulatory compliance. Troubleshoot complex data processing and system integration issues. Prepare technical documentation and support knowledge transfer activities. Work closely with Solution Architects, Technical Leads, and Application Delivery Managers to deliver enterprise-grade solutions.
Required Qualifications
Bachelor's or Master's Degree in Computer Science, Information Technology, Software Engineering, or related discipline. Minimum 5+ years of Data Engineering experience. Experience working in Banking, Financial Services, Compliance, AML, or Financial Crime projects is highly preferred. Strong experience working in Agile development environments.
Mandatory Skills
Quantexa Certified Data Engineer or Data Architect Hands-on experience with Quantexa Platform Apache Spark Scala Hadoop Ecosystem (HDFS, Hive, Pig) Elasticsearch OpenShift Container Platform (OCP) Kubernetes DevOps & CI/CD Docker Jenkins Git / BitBucket Data Integration Distributed Data Processing
Technical Skills
Big Data
Apache Spark Hadoop HDFS Hive Pig Spark SQL RDD DataFrames Datasets
Programming
Scala Python Java
Search & Analytics
Elasticsearch Data Indexing Query Optimization
DevOps & Containers
OpenShift (OCP) Kubernetes Docker Jenkins Ansible BitBucket CI/CD Pipelines
Monitoring
Grafana Prometheus Splunk
Cloud (Preferred)
AWS Microsoft Azure Google Cloud Platform (GCP)
Preferred Experience
Banking & Financial Services Compliance & AML Solutions Financial Crime Analytics Quantexa Implementation Projects Large-scale Enterprise Data Platforms Distributed Computing Performance Tuning Data Governance & Metadata Management
Key Competencies
Excellent analytical and problem-solving skills Strong debugging and troubleshooting capabilities Experience with enterprise system integration Strong understanding of software architecture and design principles Excellent communication and stakeholder management skills Ability to work independently and within cross-functional teams Strong documentation and technical writing skills
We are looking for an experienced
Quantexa Certified Data Engineer / Data Architect
to join our growing data engineering team. The ideal candidate will have strong expertise in
Quantexa, Apache Spark, Scala, Hadoop, Elasticsearch, OpenShift (OCP), and DevOps
technologies. You will be responsible for designing, developing, and optimizing enterprise-scale data processing pipelines while supporting Compliance, AML, and Financial Crime solutions.
This role requires hands-on experience with large-scale distributed systems, data integration, containerized deployments, and CI/CD practices.
Key Responsibilities
Design, develop, and maintain scalable data engineering solutions using Apache Spark, Scala, Hadoop, and Quantexa. Build high-performance data pipelines to process structured and unstructured datasets. Develop Spark applications utilizing RDDs, DataFrames, Datasets, and Spark SQL. Design and implement data transformation, enrichment, aggregation, and validation processes. Integrate Elasticsearch with Spark applications for indexing, search, and analytics. Optimize Spark jobs and Elasticsearch queries for maximum performance and scalability. Develop and maintain robust, fault-tolerant distributed data processing applications. Deploy and manage applications on OpenShift Container Platform (OCP) using Kubernetes. Collaborate with DevOps teams to implement CI/CD pipelines and automate deployments. Support SIT, UAT, deployment activities, and production cutover. Implement monitoring, logging, and performance optimization using industry-standard tools. Ensure data quality, governance, lineage, metadata management, and regulatory compliance. Troubleshoot complex data processing and system integration issues. Prepare technical documentation and support knowledge transfer activities. Work closely with Solution Architects, Technical Leads, and Application Delivery Managers to deliver enterprise-grade solutions.
Required Qualifications
Bachelor's or Master's Degree in Computer Science, Information Technology, Software Engineering, or related discipline. Minimum 5+ years of Data Engineering experience. Experience working in Banking, Financial Services, Compliance, AML, or Financial Crime projects is highly preferred. Strong experience working in Agile development environments.
Mandatory Skills
Quantexa Certified Data Engineer or Data Architect Hands-on experience with Quantexa Platform Apache Spark Scala Hadoop Ecosystem (HDFS, Hive, Pig) Elasticsearch OpenShift Container Platform (OCP) Kubernetes DevOps & CI/CD Docker Jenkins Git / BitBucket Data Integration Distributed Data Processing
Technical Skills
Big Data
Apache Spark Hadoop HDFS Hive Pig Spark SQL RDD DataFrames Datasets
Programming
Scala Python Java
Search & Analytics
Elasticsearch Data Indexing Query Optimization
DevOps & Containers
OpenShift (OCP) Kubernetes Docker Jenkins Ansible BitBucket CI/CD Pipelines
Monitoring
Grafana Prometheus Splunk
Cloud (Preferred)
AWS Microsoft Azure Google Cloud Platform (GCP)
Preferred Experience
Banking & Financial Services Compliance & AML Solutions Financial Crime Analytics Quantexa Implementation Projects Large-scale Enterprise Data Platforms Distributed Computing Performance Tuning Data Governance & Metadata Management
Key Competencies
Excellent analytical and problem-solving skills Strong debugging and troubleshooting capabilities Experience with enterprise system integration Strong understanding of software architecture and design principles Excellent communication and stakeholder management skills Ability to work independently and within cross-functional teams Strong documentation and technical writing skills