Senior Big Data Developer

Job Title: Hadoop / HPE MapR Engineer (Data Platform)Job SummaryWe are seeking a highly skilled Hadoop / HPE MapR Engineer to design, build, operate, and optimize large-scale distributed data platforms. This role is focused on supporting and enhancing HPE MapR–based ecosystems, ensuring high availability, performance, security, and reliability for enterprise data workloads.The ideal candidate will bring deep expertise in distributed systems, strong Linux administration skills, and hands-on experience managing production-grade Hadoop clusters. This is a senior-level role requiring ownership of complex initiatives, platform stability, and continuous performance optimization.Key ResponsibilitiesDesign, deploy, and manage large-scale Hadoop clusters with a focus on HPE MapR components (MapR-FS, MapR DB, MapR Streams)Administer and optimize distributed data platforms to ensure high availability, fault tolerance, and scalabilityMonitor cluster health, troubleshoot performance issues, and conduct root cause analysis for production incidentsImplement and optimize data processing frameworks including Apache Spark for batch and streaming workloadsPerform system-level tuning across Linux/Unix environments (CPU, memory, disk, and network optimization)Automate operational tasks using scripting languages such as Python, Bash, or ShellCollaborate with engineering, data, and DevOps teams to support enterprise data initiativesEnsure compliance with enterprise security, governance, and data protection standardsContribute to long-term platform strategy, capacity planning, and architectural improvementsRequired Qualifications10+ years of experience in Big Data / Data Platform EngineeringStrong hands-on experience with Hadoop distributions, specifically HPE MapRDeep understanding of distributed systems, cluster computing, and data storage architecturesProficiency in Linux/Unix system administration in large-scale environmentsHands-on experience with Apache Spark (batch and/or streaming)Strong troubleshooting skills with experience resolving performance and stability issues in production environmentsExperience with at least one programming/scripting language: Python, Java, Scala, or BashSolid understanding of cluster monitoring, logging, and incident management processesPreferred QualificationsExperience with HPE Ezmeral Data Fabric (MapR evolution)Exposure to streaming technologies (Kafka or MapR Streams)Familiarity with containerization and orchestration (Docker, Kubernetes)Experience with CI/CD pipelines and infrastructure automationKnowledge of enterprise data security, Kerberos, or Ranger-like frameworksSkills: apache,cluster,enterprise data,availability,hadoop,enterprise,linux,security,apache spark,data