BigData Platform Admin; Hadoop

Job Title

Big Data Platform Admin (Hadoop)

Irving, TX (ONSITE)

Full Time ONLY

We are looking for a highly skilled and passionate Big Data Platform Admin, who acts as a crucial liaison between the Hadoop admin team and various application development teams. The role is responsible for ensuring the optimal performance, stability, and future readiness of the Hadoop platform, focusing on strategic oversight rather than day‑to‑day administrative tasks. As a strategist it will facilitate communication, drive best practice, assess technical impacts of the platform changes, and contribute to the overall health and efficiency of the Hadoop ecosystem.

• Stakeholder Unification : Serve as a single point of contact and unified stakeholder for all Hadoop‑related concerns, bridging the gap between platform administrators and application teams.
• Review and assess upcoming Hadoop platform upgrades, including new features, libraries and patches.
• Conduct impact analysis on existing applications and services, identifying potential risks and opportunities.
• Coordinate and communicate upgrade schedules and requirements to all relevant teams.
• Technical Feature and Library Evaluation : Identify and evaluate new technical features and libraries within the Hadoop ecosystem that can benefit application teams or improve platform efficiency; propose and advocate for the adoption of new technologies and methodologies to enhance the platform’s capabilities.
• Cluster Health and Optimization : Monitor overall cluster health, performance metrics, and resource utilization; propose and implement optimization strategies to improve cluster efficiency, scalability and cost‑effectiveness; collaborate with the admin team to troubleshoot and resolve complex platform‑level issues.
• Resource Management and Housekeeping : Oversee and manage the allocation of cluster resources (CPU, memory, storage) across various applications and tenants; establish and enforce policies for resource quota management, data lifecycle and storage optimization; implement housekeeping strategies to maintain a clean and efficient cluster environment.
• Best Practices and Overall Excellence : Define, document and promote best practices for Hadoop application development, deployment and operations; ensure operational stability and resiliency of the Hadoop platform, implementing measures to prevent outages and minimize downtime; contribute in disaster recovery and business continuity plan for the Hadoop ecosystem.
• Solution Proposal and Innovation : Research and propose suitable technical solutions to address emerging business needs, performance bottlenecks, or architectural challenges within the Hadoop ecosystem; stay abreast of industry trends and advancements in big data technologies, continuously seeking opportunities for innovation.

• Education : Bachelor’s or Master’s degree in Computer Science, Engineering or a related field.
• 5+ years of experience in big data environment, with a focus on Hadoop.
• Proven experience in a technical leadership or architect role, working closely with both operations and development teams.
• Experience with distributed systems, data processing frameworks (Spark, Hive) and data warehousing concepts.
• Familiarity with the cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) is a plus.
• Deep understanding of Hadoop ecosystem components (HDFS, YARN, Map Reduce, Hive, Spark, Kafka, etc.).
• Strong understanding of Spark architecture and core concepts.
• Proficiency in Linux scripting for automation and system management.
• Basic to intermediate proficiency in Python/Scala for scripting and data manipulation.
• Experience with monitoring tools (Grafana, Prometheus) and logging frameworks.
• Awareness of various data engineering solutions and consumption tools within the big data landscape.
• Strong understanding of security best practices in a big data environment.

• Large‑scale cluster management and optimization.
• Strategic planning and stakeholder communication.
• Technical evaluation and adoption of new Hadoop features and libraries.
• Performance analysis, impact assessment, and risk mitigation.
• Resource allocation and policy enforcement.
• Documentation of best practices and disaster recovery planning.
• Innovative solution design addressing business and technical challenges.