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Job Summary
Designing and building scalable data ingestion pipelines (both streaming and batch)
Integrating with third‑party APIs, banks, and payment processors to ingest high‑volume transactional data
Writing clean, production‑quality Java 21 (Spring Boot) code for microservices and integration endpoints
Using Spring WebFlux for reactive and asynchronous processing where appropriate
Operating and optimising Kafka‑based streaming workflows and event‑driven architectures
Developing large‑scale data processing jobs on Azure Databricks using Spark (Scala/Python)
Optimising Spark workloads for performance and cost efficiency.
Designing and maintaining data schemas in MS SQL Server for analytics‑friendly querying
Ensuring data quality, lineage, governance, and monitoring
Exposing trusted data products via APIs for micro‑frontends and reporting tools
Embedding pre‑built data science solutions into our data estate
Providing Level 3 production support when required
Collaborating cross‑functionally to turn business needs into reliable, production‑ready pipelines
Skills & Experience:
Strong experience in Jave 21+, Spring and Spring Boot
Hands on experience with messaging and streaming platforms (Apache Kafka or equivalent), Azure Event Hubs
Solid T-SQL skills with MS SQL Server experience
Passion for clean design, quality code, testing (Junit, Cucumber), Git and Agile delivery
Familiar with Cosmos DB or other NoSQL technologies
Experience with Terraform, CI/CD and GitOps pipelines
Qualification:
A Bachelors degree in Computer Science, Computer Engineering, Chemical Engineering, Mathematics or a related qualification
Contact Penny Janse Van Rensburg on 021 418 1750, quoting the Ref: CTI006510.
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