Senior Data Engineer - (Flink/Kafka/PySpark)

About this role

We are looking for an experienced Data Engineer with strong expertise in real-time data streaming and distributed data processing technologies. The ideal candidate should have hands-on experience in building scalable, event-driven data platforms using Apache Flink, Kafka, Java/Scala, and PySpark. The candidate will be responsible for designing, developing, and maintaining high-performance data engineering solutions within large-scale enterprise environments. Requirements Key Responsibilities: Design, develop, and maintain real-time streaming data pipelines and event-driven architectures. Build scalable and fault-tolerant data engineering solutions using Apache Flink, Kafka, and Java/Scala. Develop and optimize distributed data processing applications for enterprise-grade systems. Implement best practices for performance tuning, resiliency, security, and compliance requirements. Collaborate with cross-functional teams to design technical and application architectures. Ensure production-grade monitoring, troubleshooting, and operational excellence of distributed services. Contribute to CI/CD implementation and DevOps best practices. Work closely with engineering teams to drive technical improvements and architectural decisions. Mandatory Technical Skills: Minimum 4+ years of development and design experience in: Apache Flink Java or Scala Apache Kafka PySpark Real-time data streaming technologies Event-driven architectures Hands-on experience with: Apache Flink (Beam or Spark Streaming experience is also valuable) Kafka ecosystem and streaming platforms JVM tuning and performance optimization Distributed systems design and implementation Docker and Kubernetes containerization Linux OS administration and Shell scripting SQL and NoSQL databases CI/CD tools such as GitHub and Jenkins Design patterns and their implementation Production monitoring and troubleshooting of distributed services Nice to Have Skills: Redis or other caching technologies. Experience with Spark Streaming or Apache Beam. Experience working with banking or fintech platforms. Data Engineering & Security Requirements: Strong understanding of data security principles and controls. Experience implementing secure data transfer mechanisms including: CRON jobs ETL processes JDBC and ODBC scripts Knowledge of encryption, anonymization, data integrity, and policy controls in large-scale infrastructures. Understanding of data sensitivity requirements, including: Protection of PII data Secure logging practices Secure in-memory data handling Ability to identify security design gaps and recommend enhancements. Experience implementing wrapper solutions for legacy or third-party components to ensure compliance requirements are met. Infrastructure & Networking Knowledge: Working knowledge of: DNS Proxy servers ACLs Networking policies Troubleshooting network-related issues Functional Requirements: Experience working in Agile environments. Ability to design and implement scalable technical architectures. Conduct technology research and benchmarking activities. Ability to influence engineering teams on technical best practices. Experience working in enterprise-scale environments. Banking, Financial Services, or FinTech domain experience is preferred. Soft Skills: Excellent communication and interpersonal skills. Strong problem-solving and analytical abilities. Self-driven and capable of working independently. Ability to collaborate effectively with cross-functional teams and stakeholders. Strong presentation and listening skills. Positive attitude and ability to foster a collaborative team environment. Passionate about engineering excellence and continuous improvement.