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• Orchestrated Hadoop and Spark cluster environments (CDP – 7.1.8) with precision, overseeing cluster sizing, configuration, smoke testing, security setup, and ongoing performance tuning. • Ensured seamless cluster operations, adeptly managing minor and major upgrades, along with OS patching, to maintain peak system performance. • Spearheaded the migration of CDH and HDP clusters to CDP (Cloudera Data Platform), showcasing expertise in seamless transition. • Implemented Python scripts for data processing tasks and automation, enhancing cluster management efficiency.• Provided detailed reports on resources/services utilization and performance metrics, empowering user communities with actionable insights. • Facilitated coordination with Vendor teams for seamless installation, bug fixes, upgrades, and escalations, ensuring minimal downtime. • Supported Data Engineering teams in the deployment of Hadoop/Spark jobs (DevOps model support), leveraging performance tuning techniques for optimal job execution. • Contributed to the evolution of systems architecture to meet evolving requirements for scaling, reliability, performance, and manageability. • Demonstrated proficiency in administering Hive, Spark, Sqoop, HBase, and Kafka, ensuring the smooth operation of critical data processing components. • Leveraged expertise in networking/security infrastructure, encompassing VLAN, firewalls, Kerberos, LDAP, ensuring robust system defense. • Extensive experience in administering Red Hat Enterprise Linux environments, ensuring stability and security across the system landscape. • Proficient in Version Control tools such as git, facilitating collaborative development and code management.Environment: MapR 6.1, MEP 6.0.0, RHEL 7.0, RDS, Ec2 r3.4xlarge, EMR-5.8.0, MS-SQL, MaprFS, Hive, Zookeeper, Oozie, MapReduce, Yarn, Nagios, Sqoop, Hue, Drill, Spark, HBase

• Big Data Engineer in MapR distribution with Multiple clusters which included Dev clusters and PROD clusters and Disaster Recovery.• Enterprise Data DEV & PROD cluster upgraded from Mapr 6.x to Mapr 6.1• Enterprise Data DEV & PROD cluster upgraded from MEP 5.x to 6.0• Responsible for Cluster maintenance, commissioning and decommissioning Data nodes, Cluster Monitoring, Troubleshooting, Manage & review Hadoop log files.• Responsible for Performing Filesystem Checks time to time to check any over-replicated blocks, under replicated blocks, miss-replicated blocks, corrupt blocks and missing replicas.• Linux-based implementations such as Operating System patching RHEL 7.x to 7.5.• Responsible for Installation, Configuration, Implementation, Upgradation, Maintenance& Troubleshooting of application servers and good experience in clustering.• Creating and maintaining user accounts, profiles, security, rights, disk space and monitoring.• Automated deployment and maintenance tasks using Python and Ansible, significantly reducing manual intervention.• Developed shell scripts for system monitoring and maintenance, enhancing system reliability and uptime• Implementation in Hive and its components and troubleshooting if any issues arise with Hive.• Server Consolidation and Migration of Applications on Mysql and Java Applications and SSL certificates.• Enabled Mapr Security across the cluster.• Evaluated MaprDb with Security across the cluster for major use cases across the enterprise.• Responsible for cluster availability and experienced on ON-call support.• Experienced in production support which involves solving the user incidents varies from sev1 to sev5Environment: MapR 5.1.0, MapR 6.1, MEP 2.0.3, MEP 6.0.0, RHEL -7.0, RDS, Ec2 r3.4xlarge, EMR-5.8.0, MS-SQL, MaprFS, Hive, Zookeeper, Oozie, MapReduce, Yarn, Nagios, Sqoop, Hue, Drill, Spark, Hbase.

• Migrating an existing on-premises application to Amazon AWS. • Designing and deploying scalable, highly available and fault tolerant systems on Amazon AWS in different region/zone. • Implementing Auto-scaling groups for different clusters using the Amazon Auto-scaling feature in Amazon EC2.• Creating custom VPC, S3 Bucket & Route 53.• Monitoring system metrics (CPU, Memory, Disk I/O, Network I/O) using Amazon CloudWatch and take appropriate actions.• Evaluating and implementing MapR distribution of Hadoop for production environment. • Implementing ACE ‘security protocols and patches provided by MapR. • Ensuring data integrity and security and reporting new issues to MapR support team. • Creating and managing users and groups access. • Leveraged Python for data processing and analysis tasks, facilitating informed decision-making processes.• Developed Python scripts to automate routine tasks and system monitoring, improving operational efficiency by 30%.• Utilized Ansible for configuration management, ensuring scalable and consistent deployment of applications across various environments.• Implemented Shell Scripting for automated build and deployment processes, reducing deployment time by 50%.• Monitoring increasing workload and capacity planning. • Analyzing newly discovered system failures, identifying root causes, and recommended course of actions. • Creating ingest patterns for importing data from legacy systems such as DB2, Oracle, SQL.Environment: MapR 5.1.0, MapR 6.1, MEP 2.0.3, MEP 6.0.0, RHEL -7.0, RDS, Ec2 r3.4xlarge, EMR-5.8.0, MS-SQL, MaprFS, Hive, Zookeeper, Oozie, MapReduce, Yarn, Nagios, Sqoop, Hue, Drill, Spark, Hbase.

• Hadoop administrator in Hortonworks distribution with 6 clusters which included POC clusters and PROD clusters.• Automated deployment and configuration management tasks using Ansible, significantly reducing manual intervention and ensuring consistency across environments.• Developed Python scripts to automate routine tasks, resulting in a 40% increase in operational efficiency.• Created Python scripts for comprehensive system monitoring and data analysis, enhancing operational insights and proactive issue resolution.• Utilized Shell Scripting for system monitoring and maintenance, enhancing system reliability and uptime.• Collaborated with DevOps teams to integrate Ansible playbooks into CI/CD pipelines, streamlining the deployment process• Big Data DEV & PROD cluster upgraded from HDP 2.3.x to HDP2.5.x• Big Data DEV & PROD cluster upgraded from Ambari 2.1.x to 2.5.x.x• Monitoring and controlling local file system disk space usage, log files, cleaning log files with automated scripts. • Automated all the jobs for pulling data from FTP server to load data into Hive tables, using Oozie workflows. • Integrated Apache Storm with Kafka to perform web analytics. Uploaded click stream data from Kafka to Hdfs, Hbase and Hive by integrating with Storm.• Backed up data on regular basis to a remote cluster using distcp.• Linux-based implementations such as Operating System patching RHEL6.x to 6.8.• Responsible for Installation, Configuration, Implementation, Upgradation, Maintenance & Troubleshooting of application servers and good experience in clustering.• Creating and maintaining user accounts, profiles, security, rights, disk space and monitoring.Environment: Hortonworks, Ansible, Python, HDP 2.5.3, Ambari 2.5.0.3, RHEL -6.8, Oracle 12g, MS-SQL, Hadoop, Hive, Zookeeper, Oozie, MapReduce, Yarn, Nagios, Sqoop, Hue, BigData.