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Popular data-engineer role, mid-level experience, metro location, and broad streaming skillset drive high competition.
Core streaming and data engineering skills are industry-transferable, so background fit sensitivity is low.
Explicit 4+ years plus many mandatory technologies and security/compliance requirements increase shortlisting strictness.
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Design, develop, and maintain real-time streaming data pipelines using Apache Flink, Kafka, and Java/Scala within large-scale enterprise environments.
Build scalable, fault-tolerant distributed data processing applications with focus on performance tuning, resiliency, security, and compliance.
Ensure production-grade monitoring, troubleshooting, and contribute to CI/CD and DevOps practices for distributed data services.
Minimum 4+ years of development and design experience in Apache Flink, Java or Scala, Apache Kafka, PySpark, and real-time data streaming technologies.
Hands-on experience with JVM tuning, Docker, Kubernetes, Linux OS administration, Shell scripting, SQL/NoSQL databases, CI/CD tools (GitHub/Jenkins), and production monitoring of distributed services.
Strong understanding and practical implementation experience of data security principles, secure data transfer, and compliance mechanisms in large-scale infrastructures.
Experience working in enterprise-scale environments; Banking, Financial Services, or FinTech domain experience preferred but not mandatory.
Experienced in building event-driven, scalable technical architectures in real-time streaming and distributed data ecosystems.
Proven ability to influence engineering teams on best practices and architectural decisions in Agile, enterprise environments.
Demonstrated expertise in security controls related to PII data protection, secure logging, and data policies for compliance in data engineering solutions.