Department/Team: Engineering 
Clearance Requirement:  Not Required - Must be eligible
Location: Remote
Employment Type: Full-time, Salaried

Role Summary

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.

Required Qualifications

• 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

 

Preferred Qualifications

• 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)