Big Data/Data Platform Site Reliability Engineer (Hadoop/Kafka)

TL;DR

Senior Site Reliability Engineer (Hadoop/Kafka): Deploying, configuring, and maintaining big data stores and large-scale Linux infrastructure with an accent on reliability, scalability, and operational excellence. Focus on debugging complex distributed system issues, advancing technology stack, and ensuring maximum uptime and predictable performance.

Location: Willing and able to work East Coast U.S. hours (9am–6pm EST)

Company

hirify.global is a fast-growing healthcare technology company using real-time data to transform healthcare through machine learning and programmatic automation.

What you will do

• Deploy, configure, monitor, and maintain multiple big data stores with a strong focus on reliability and scalability.
• Manage large-scale Linux infrastructure to ensure maximum uptime and predictable performance.
• Develop and document system configuration standards, operational procedures, and best practices.
• Perform performance and reliability testing, including reviewing configuration and hardware specifications.
• Participate in incident response, root cause analysis, and drive long-term reliability improvements.
• Advance the technology stack with innovative ideas and pragmatic solutions.

Requirements

• Strong hands-on experience operating large-scale Linux infrastructure in production (Rocky Linux or equivalent).
• Deep practical knowledge of Apache Hadoop-based data platforms (HDFS architecture, Kerberos, operational lifecycle).
• Experience running Apache Kafka clusters in production, including KRaft-based setups.
• Proven ability to debug complex distributed system issues across storage, compute, and networking layers.
• Experience designing or improving automation, deployment, or GitOps-style workflows.
• Proficiency in scripting or automation (Python, Shell).
• Solid understanding of networking fundamentals (TCP/IP, DNS, load balancing, basic network security).
• Willing and able to work East Coast U.S. hours (9am–6pm EST).

Nice to have

• Experience with Trino and Iceberg as large-scale analytical query engines.
• Experience administering Percona XtraDB Cluster or other HA databases.
• Hands-on experience with Ceph or other distributed storage systems.
• Strong background in observability platforms (Prometheus, Grafana, Graphite, ELK, Icinga).
• Experience with configuration management (Puppet or similar).
• Familiarity with Docker and Kubernetes in production environments.
• Background in AdTech, real-time data systems, or low-latency/high-throughput environments.

Culture & Benefits

• A collaborative environment where team success is valued.
• Opportunities to continuously grow skills and learn new technologies.
• Emphasis on strategic thinking and deep dives into complex systems.
• A proactive approach to problem-solving and infrastructure reliability.

Hiring process

• Initial Screening Call (30 mins).
• Team Lead Screening (30 mins).
• Technical Interview with SREs (1 hour).
• General Discussion with VP of Data Engineering (30 mins).
• Technical Interview with Principal Architect (1 hour).
• Meet & Greet w/ SVP of Engineering (15 mins).
• Final Video Call with Sr. Director of Data Management at WebMD (30 mins).