Project Description:A next-generation cross-asset data management platform to provide globally consistent data and innovative tools to support business strategy for trade/sales clients that is built on big data architecture, highly scalable, and cloud-ready. The platform enables industry-leading analytics, client reporting, regulatory compliance, surveillance, supervisory reporting, and data science solutions (data flame). The project tech stack: Apache Spark, Hive, Java, Scala, Spring, SQL, Kafka, Hadoop.
We are looking for a strong Senior Java Developer with Big Data experience (Hadoop, Spark) capable of build the design and establish the framework in order to expose and distribute the Risk data to wide variety of consumers including Finance, Front office Risk Systems, Trading Systems, Back office and Account systems. This should cover low latency access and Streaming, Push / Pull mechanisms depending on the type of consumers.
The role of the Senior Java Developer involves working with strong development teams (3 Senior Java Developers), the opportunity to work with big data improving knowledge in this domain utilizing the resources of an international bank.
Responsibilities: * Design and build frameworks for ingesting/modeling the complex Risk data * Develop Low latency caching to service Front office risk systems
Mandatory Skills Description: * At least 5 years of experience in software development, including professional backend software development experience; * Strong Knowledge of the Java programming languages * Understanding Java dependency injection frameworks, preferably Spring * Strong SQL skills * 1+ year of Big data development with extensive hands-on experience with Spark programming * Strong knowledge of big data technologies like Hadoop (Hive) and Spark * Understanding Data governance * Should be familiar with algorithms and design patterns * Understanding of distributed systems. * Understanding of CI/CD workflow. * Familiarity with the Linux environment, including scripting skills
Nice-to-Have Skills Description: * Databricks and cloud services, preferably aws/gcp * Experience with in-memory databases and caching * Data modeling: fact, dimension tables, SCD * Understanding of open table formats: iceberg, delta lake, hudi * Understanding of open file formats: parquet, orc * Job Orchestration tools like Autosys or Airflow * Financial background (where possible)
