Company Overview:

Navikenz India Private Limited is a specialized technology services firm focused on driving digital transformation through advanced data engineering, cloud-native development, and intelligent automation. The company partners with global enterprises to modernize their data ecosystems, enabling them to derive actionable insights from complex, high-velocity information streams. Operating at the intersection of engineering excellence and business strategy, Navikenz fosters a culture of technical rigor and innovation, supporting clients across diverse sectors including finance, retail, and manufacturing to build scalable, future-ready digital platforms.

Role Overview:

As a Data Streaming Engineer, you will be at the forefront of designing and implementing high-throughput, low-latency data pipelines that power real-time decision-making for our enterprise clients. You will collaborate closely with cross-functional teams, including data architects, product managers, and infrastructure engineers, to translate complex business requirements into robust streaming architectures. Your work will directly influence the speed and reliability of data delivery, ensuring that our clients can process and act upon massive datasets instantaneously, thereby driving significant operational efficiency and competitive advantage.

Key Responsibilities:

- Architect and deploy scalable streaming solutions using Spark Streaming and Apache Flink to handle high-volume data ingestion and processing requirements for global clients.

- Develop and maintain resilient messaging architectures using Kafka to ensure seamless data flow and fault tolerance across distributed systems.

- Optimize streaming applications for performance and cost-efficiency, ensuring minimal latency in data delivery to downstream analytical platforms.

- Collaborate with stakeholders to define data schemas and integration patterns that align with long-term business intelligence objectives.

- Implement rigorous monitoring, logging, and alerting frameworks to maintain high availability and data integrity within production environments.

- Mentor junior engineers and contribute to the internal engineering culture by promoting best practices in code quality, documentation, and system design.

Required Skillset:

- Demonstrated expertise in building and managing real-time data pipelines using Spark Streaming, Kafka, and Apache Flink within large-scale production environments.

- Strong proficiency in Java for developing high-performance, maintainable backend services and streaming applications.

- Proven ability to design distributed systems that are highly available, fault-tolerant, and capable of handling significant data throughput.

- Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders and collaborate effectively within a team.

- A proactive approach to problem-solving, with the capacity to adapt to evolving project requirements and work effectively in a hybrid setup in Bangalore.

- A solid academic foundation in Computer Science or a related quantitative field, complemented by 5 to 16 years of hands-on experience in data engineering and streaming technologies.