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Wissen Logo Wissen · IT - Software Development

System Engineer

India, Haveli · Job Posted March 05, 2026
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Job Description

We are looking for an experienced System Engineer with strong hands-on expertise in building and managing real-time and batch data processing systems. The ideal candidate must have deep specialization in at least one distributed data technology—Apache Flink, Apache Kafka, Spark Structured Streaming, or Dremio—along with solid working knowledge of the others. This role requires strong experience in distributed systems, event-driven architectures, streaming data pipelines, and observability of production-grade data platforms.

Job Responsibility

  • Design, build, and optimize real-time streaming pipelines and batch workloads
  • Ensure data correctness, reliability, and processing guarantees (at-least-once / exactly‑once)
  • Develop stateful stream processing solutions including joins, aggregations, windowing, and CDC pipelines
  • Build and operate scalable, low‑latency event-driven architectures using technologies like Flink, Kafka, Pulsar, or Spark
  • Design and support semantic layers, distributed SQL engines, and query acceleration using Dremio
  • System Integration
  • Data Lakes (Iceberg, Delta Lake)
  • OLAP / Analytical Query Engines
  • Downstream applications, APIs, and data consumers
  • Manage schema evolution and compatibility across producers and consumers (Schema Registry, formats, versions)
  • Monitor, troubleshoot, and performance‑tune distributed data processing jobs in production environments
  • Implement observability standards across streaming platforms and distributed components

Requirements

  • Expert-level knowledge in at least one of the following: Apache Flink, Apache Kafka, Spark Structured Streaming, or Dremio (Trino/Presto/Drill)
  • Strong hands-on experience in real-time and batch data processing systems
  • Solid understanding of distributed systems, scalability, and fault-tolerant architectures
  • Experience building and operating event-driven architectures
  • Proficiency in managing schema evolution and compatibility across streaming ecosystems
  • Hands-on experience integrating data pipelines with data lakes, OLAP engines, and downstream applications
  • Strong skills in troubleshooting, performance tuning, and optimizing distributed data processing jobs
  • Knowledge of observability practices across streaming and distributed systems
  • Strong analytical, problem‑solving, and communication skills

Nice to have

  • Experience with Pulsar, Redpanda, or other distributed messaging systems
  • Knowledge of Kubernetes, containerized deployments, and orchestration
  • Exposure to cloud platforms (AWS, Azure, GCP) and their managed streaming services
  • Familiarity with CI/CD pipelines and DevOps practices
  • Hands-on experience with data governance, lineage, and cataloging tools
  • Knowledge of SQL performance tuning and BI acceleration mechanisms
  • Understanding of Data Mesh or distributed data ownership models
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