Data Systems Engineer – ELK/Kafka/Linux

This is a hands-on, client-facing engineering role within the Real-Time Operations Intelligence (RTOI) team, supporting large-scale streaming data platforms. The position requires close collaboration with cross-functional teams and support for hundreds of internal users, so strong communication skills and a team-oriented mindset are essential.

Below is a brief overview of the position:

Job Title: Data Systems Engineer – ELK/Kafka/Linux
Location: Alpharetta, GA or Menlo Park, CA (Onsite)

Experience Level: 7–15 years

Required Qualifications:

• 7+ years of overall IT/application development experience

• 5+ years of hands-on coding experience in at least one language: Python (preferred), Ruby, Shell, Java, C/C++, or Go

• Minimum 2+ years of data engineering experience with Kafka

• Strong working knowledge of Linux platform (application deployment, debugging, performance tuning, CPU/memory troubleshooting)

• Experience building and supporting real-time ETL/streaming pipelines using Kafka and ELK (Elasticsearch/Logstash/Kibana)

• Experience running, deploying, and supporting applications in large-scale Linux cluster environments

• Strong understanding of distributed systems architecture, scalability, and Kafka ecosystem design trade-offs

• SQL and database experience

• Ability to handle full software development lifecycle (requirements, design, implementation, testing, deployment, and support)

• Strong debugging and production support experience (ensuring jobs are up and running for hundreds of users)

• Excellent communication skills, team-oriented mindset, and strong curiosity/learning ability

Preferred Qualifications:

• Experience with Snowflake database

• Spark data processing experience

• Hadoop ecosystem exposure

• Observability and data analysis background

• AWS or other cloud technologies

• ELK certification

• Financial industry experience (nice to have)

• Bachelor’s degree (strong plus, not required)

Key Responsibilities:

• Design and develop large-scale streaming ETL pipelines using Kafka and ELK

• Deploy and manage applications in Linux-based production environments

• Ensure scalability and reliability within Kafka cluster environments

• Support hundreds of internal stakeholders and dashboards with real-time data needs

• Troubleshoot and debug production issues across distributed systems

• Work across on-prem and cloud-based platforms

• Contribute to development, deployment, and ongoing operational support

This role requires a well-rounded data engineer with strong core application development skills—not just scripting ability—who thrives in large-scale distributed Linux environments.