Senior Data Engineer - Streaming
Listed on 2026-05-30
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Software Development
Data Engineer
Department/Team: Engineering
Clearance Requirement: Not Required - Must be eligible
Location: Remote
Employment Type: Full-time, Salaried
We are seeking a Senior Data Engineer to design and build high-performance real-time data platforms that power analytics, machine learning, and operational intelligence. This role focuses on streaming data pipelines, distributed processing, and large-scale event data systems.
You will work on building and operating low-latency data pipelines using technologies such as Apache Flink, Apache Druid, Kafka, and modern data infrastructure, enabling real-time insights across large volumes of structured and unstructured data.
This role requires strong experience in stream processing architectures, distributed systems, and scalable data infrastructure.
Key Responsibilities:- Design and implement real-time streaming data pipelines for high-volume event data.
- Develop and operate distributed data processing systems using technologies such as:
- Apache Flink
- Apache Kafka
- Apache Druid
- Build scalable ingestion pipelines capable of handling millions of events per second.
- Design low-latency analytical data stores for operational dashboards and real-time analytics.
- Optimize data pipelines for performance, scalability, and fault tolerance.
- Work with product and analytics teams to translate business needs into real-time data models.
- Build and maintain data observability, monitoring, and reliability frameworks.
- Implement schema evolution and data quality controls across streaming pipelines.
- Contribute to data platform architecture decisions and infrastructure design.
- Mentor junior engineers and promote best practices in data engineering and distributed systems.
- 7+ years of experience in data engineering or distributed systems development
- Strong experience building streaming data pipelines
- Hands-on experience with at least one major streaming framework
- Experience with real-time analytical databases
- Experience with large-scale distributed systems
- Strong SQL skills and experience designing analytical data models
- Experience building fault-tolerant, highly scalable pipelines
- Proficiency in one or more programming languages:
- Java
- Python
- Experience with AWS
- Experience operating Apache Flink clusters in production
- Experience with Apache Druid real-time ingestion
- Experience building low-latency OLAP analytics systems
- Experience with Kubernetes-based data infrastructure
- Experience with Iceberg / Hudi / Delta Lake
- Experience with real-time ML feature pipelines
- Experience building observability for data platforms
- Experience with high-volume event streams (billions of events/day)
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