Data Engineer
Posted 8 Oct 2026
Advertised as “Quantexa Data Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
No salary listed for this role.
CertificationsQuantexa Certified Data Engineer
Field of studyComputer Science, Information Technology, Software Engineering (or related)
Study levelBachelor's or higher
Role Overview
We are seeking a talented and experienced Data Engineer with strong expertise in Quantexa, Hadoop, Scala, Apache Spark, Elasticsearch, OpenShift Container Platform (OCP), and DevOps practices.
The successful candidate will be responsible for designing, developing, optimizing, and maintaining scalable big data solutions using Apache Spark, Scala, Hadoop, and Elasticsearch. The role involves collaborating with cross-functional teams to build efficient data processing pipelines and search applications.
Knowledge and experience in the Compliance / AML domain will be an added advantage.
Key Responsibilities
- Design, develop, and implement Spark/Scala applications and data processing pipelines for large volumes of structured and unstructured data.
- Implement data transformation, aggregation, enrichment, and computation processes to support analytics and machine learning initiatives.
- Collaborate with cross-functional teams to understand data requirements and translate them into effective data engineering solutions.
- Integrate Elasticsearch with Spark for efficient data indexing, querying, and retrieval.
- Implement transformations and aggregations using Spark RDDs, DataFrames, Datasets, and Spark SQL.
- Develop scalable, reliable, and fault-tolerant Spark applications following industry best practices and coding standards.
- Optimize and tune Spark jobs and Elasticsearch queries to improve performance, scalability, and resource utilization.
- Monitor job performance, identify bottlenecks, troubleshoot issues, and implement appropriate optimizations.
- Troubleshoot and resolve issues related to data processing, data quality, Spark performance, and Elasticsearch integration.
- Ensure data quality, consistency, accuracy, and integrity throughout the data processing lifecycle.
- Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration technologies.
- Optimize data engineering workflows for containerized environments and efficient resource utilization.
- Collaborate with DevOps teams to streamline deployments and implement CI/CD pipelines.
- Implement data governance, data lineage, and metadata management practices to ensure data accuracy, traceability, and compliance.