Data Operation Engineer

Key Responsibilities

Build, maintain, and optimize scalable data pipelines for high-throughput applications

Support operational health of data systems, ensuring reliability and uptime

Develop and enhance backend services using C# and Python

Manage and query large datasets in Snowflake and Google BigQuery environments

Deploy and maintain containerized applications using Docker in Linux-based systems

Integrate and manage streaming/data messaging systems such as Kafka (Confluent) and RabbitMQ

Monitor pipeline performance, troubleshoot issues, and implement improvements

Collaborate with cross-functional teams to ensure smooth data operations and deployments

Required Qualifications

5+ years of experience in infrastructure and software engineering with exposure to data engineering and pipelines

Proficiency in C# and Python

Hands-on experience with Snowflake and/or Google BigQuery

Strong experience working in Linux/Unix environments and Docker

Experience building and maintaining data pipelines

Familiarity with distributed messaging systems such as Confluent Kafka or RabbitMQ

Ability to work independently in a remote environment while communicating effectively

Preferred Qualifications

Experience with Elastic/ELK stack for logging and monitoring

Familiarity with Terraform for infrastructure as code

Experience with Kubernetes for container orchestration

What Success Looks Like

Reliable, efficient data pipeline operations with minimal downtime

Improved observability and monitoring of data systems

Timely resolution of production issues and performance bottlenecks

Well-documented systems and processes for maintainability

Work Environment

Fully remote team with flexible collaboration

Fast-paced, engineering-driven culture

Opportunity to work on modern data platforms and distributed systems