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Specialized real-time streaming skills balanced by a common data-engineer title, leading to moderate competition.
Streaming data engineering skills (Kafka/Flink/PySpark) are broadly transferable across industries, so low sensitivity.
Multiple mandatory streaming technologies and language requirements plus seniority make shortlisting filters stringent.
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Design, develop, and maintain scalable real-time data pipelines using Apache Kafka, Apache Flink, Java, and PySpark.
Build and optimize high-throughput, low-latency streaming applications supporting business and regulatory workloads.
Collaborate with architects, platform teams, and stakeholders to deliver secure, fault-tolerant, and maintainable streaming data solutions.
Strong hands-on experience with Java, Python, Apache Kafka, Apache Flink, PySpark, and real-time streaming architectures.
Bachelor's or Master's degree in Computer Science, IT, Data Engineering, or equivalent industry experience.
Experience designing and operating scalable distributed real-time data systems and data pipelines.
Work Experience Required: Not explicitly mentioned in the JD.
Proven expertise in building and maintaining enterprise-scale streaming data platforms with focus on performance, scalability, and fault tolerance.
Experience collaborating in agile environments and interfacing across engineering, analytics, and business teams.
Background or exposure to Risk & Compliance or Business Platform data ecosystems preferred.