Senior Data Engineer

Develop, test, validate and maintain, scalable batch and real-time data processing applications using Apache Spark, Kafka, and NiFi.
Build validation suite for high-performance, fault-tolerant, and resilient distributed systems capable of handling large data volumes.
Develop reusable frameworks, libraries, and shared platform components to accelerate engineering productivity.
Translate business and technical requirements into scalable software solutions.
Contribute to architecture discussions, technical designs, and engineering standards.

Streaming & Data Platform Engineering
Create and implement validation suite for Spark batch and streaming applications to process high-volume datasets efficiently.
Validate and support Apache NiFi data ingestion, transformation, and routing workflows.
Build reliable data pipelines supporting real-time and near-real-time processing requirements.
Implement solutions for data replay, recovery, checkpoint management, and failure handling.

Performance & Scalability
Analyze system bottlenecks and optimize application performance, throughput, and resource utilization.
Improve scalability, reliability, and availability of distributed applications.
Develop and test solutions leveraging modern storage technologies including Apache Ozone, Ceph, and cloud-native storage platforms.
Build deployment automation and operational tooling to improve platform reliability.
Monitor production environments and proactively address operational concerns.
Participate in troubleshooting, root-cause analysis, and incident resolution activities.

Engineering Excellence
Participate in code reviews and promote engineering best practices.
Maintain high-quality documentation for systems, APIs, and platform components.
Collaborate closely with Product, Architecture, Platform, and DevOps teams.
Contribute to CI/CD processes and continuous improvement initiatives.
Mentor junior engineers and foster a culture of technical excellence and innovation.