Big Data Infrastructure Engineer

Job Overview
We are seeking a Big Data Infrastructure Engineer with a strong AI-first and automation-driven mindset to join our
infrastructure team and support the administration and operation of enterprise Big Data platforms and their underlying
infrastructure.
The ideal candidate should have strong hands-on experience in Linux operating system administration and database
administration, with particular focus on configuration, troubleshooting, performance tuning, optimization, monitoring,
and production support.
The candidate is expected to actively leverage AI-assisted tools and automation to improve troubleshooting,
operational efficiency, scripting, documentation, research, and day-to-day engineering activities, while maintaining
the technical judgment required to validate solutions before implementation.
The role also requires practical knowledge of Docker and Kubernetes, along with a good understanding of clustering,
high availability, distributed systems, and Big Data concepts. A strong willingness to continuously learn and stay
current with emerging AI, automation, infrastructure, and Big Data technologies is essential.

Duties and Responsibilities
• Leverage AI-assisted tools to improve troubleshooting, log analysis, scripting, documentation, research, and
operational efficiency while validating outputs before implementation.
• Identify repetitive operational activities and develop automation solutions using Shell/Bash, Python, Ansible,
APIs, or other appropriate technologies.
• Continuously evaluate emerging AI and automation capabilities and identify practical opportunities to improve
infrastructure operations and engineering workflows.
• Administer, configure, manage, troubleshoot, and optimize Linux operating systems supporting production and
non-production environments.
• Monitor and analyze CPU, memory, disk, filesystem, network, processes, and system services, and perform
configuration and performance tuning when required.
• Administer and manage PostgreSQL, MySQL/MariaDB, and Redis, including configuration, access management,
backup and recovery, monitoring, troubleshooting, maintenance, and performance optimization.
• Support database replication, high availability, backup/recovery, and capacity management requirements.
• Support and maintain Docker and Kubernetes environments, including deployment, configuration, monitoring,
troubleshooting, scaling, and cluster administration.
• Support clustered and distributed platforms with focus on high availability, replication, failover, load
balancing, quorum, capacity management, and disaster recovery.
• Support the installation, configuration, monitoring, administration, and upgrade of Cloudera/Hortonworks and
Hadoop-based environments.
• Support and troubleshoot Hadoop ecosystem components such as HDFS, YARN, Hive, Spark, HBase, and
Kafka, as well as related platforms such as Airflow, Superset, and Trino/Presto where applicable.
• Perform production monitoring and support using tools such as Zabbix and Grafana, and participate in incident
management, root cause analysis, and corrective/preventive actions.
• Support security integrations and technologies such as Ranger, LDAP, and Kerberos.
• Collaborate with development, infrastructure, and other technical teams on deployments, upgrades,
infrastructure changes, troubleshooting, and production support.
• Maintain technical documentation, operational procedures, automation, and infrastructure configuration records.
Skills and Qualifications
• 3-5 years of relevant hands-on experience in Linux/System Administration, Database Administration, Big Data
Infrastructure, DevOps, or a related infrastructure role.
• Bachelor's Degree in Computer Science, Computer Engineering, Information Technology, or a related field.
• Strong AI-first and automation-driven mindset, with demonstrated ability to use AI-assisted tools effectively in
technical workflows and critically validate generated recommendations before applying them.
Big Data Infrastructure Engineer - Job Description
Good scripting and automation skills using Shell/Bash; knowledge of Python, Ansible, APIs, or similar
technologies is highly desirable.
• Strong hands-on knowledge of Linux administration, including system configuration, service management,
resource management, storage/filesystems, permissions, networking, troubleshooting, and performance
optimization.
• Good hands-on knowledge of PostgreSQL, MySQL/MariaDB, and Redis administration, including configuration,
backup and recovery, users and privileges, monitoring, maintenance, and performance tuning.
• Good understanding of database concepts including connections, transactions, locks, indexing, query
performance, replication, and high availability.
• Good hands-on understanding of Docker and Kubernetes, including containers, images, pods, deployments,
services, storage, networking, monitoring, resource management, and troubleshooting.
• Good understanding of clustering and distributed system concepts, including high availability, replication,
failover, load balancing, and quorum.
• Good understanding of networking fundamentals, including TCP/IP, DNS, ports, routing, connectivity, and
network troubleshooting.
• Good understanding of Big Data concepts and the Hadoop ecosystem, with familiarity or hands-on experience
in HDFS, YARN, Hive, Spark, Kafka, and HBase.
• Familiarity with Cloudera or Hortonworks platforms is highly desirable.
• Familiarity with Zabbix/Grafana, Ranger/LDAP/Kerberos, CI/CD tools, and Trino/Presto is an advantage.
• Strong troubleshooting, analytical, and problem-solving skills, with the ability to investigate issues
systematically and identify root causes.
• Ability to work effectively in production environments, collaborate across technical teams, take ownership of
assigned activities, and continuously develop technical knowledge.

Preferred Certifications
• Relevant Linux certifications such as RHCSA or RHCE.
• Kubernetes certification such as CKA.
• PostgreSQL or MySQL-related certifications/training.
• Red Hat Ansible or other relevant automation certifications.

Note: Certifications are considered an advantage and are not a substitute for practical hands-on experience.