LigaData

Big Data Infrastructure Engineer

LigaData

Software Development · 51-200 employees

Yesterday
Remote Mid (2-5 yrs) Full-time
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About the role

The role involves administering and optimizing enterprise Big Data platforms and their underlying infrastructure using automation and AI-assisted tools. You will be responsible for managing Linux systems, databases, and containerized environments while ensuring high availability and performance.

What they look for

Linux Administration Database Administration Big Data Infrastructure Kubernetes Docker Python Ansible Shell/Bash PostgreSQL MySQL Redis Hadoop Spark Kafka Automation AI-assisted tools

Requirements

Candidates must have 3-5 years of experience in Linux system administration, database management, or Big Data infrastructure. A bachelor's degree in a technical field and strong proficiency in scripting, automation, and distributed systems are required.

Full description

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.