Job Description

:Job Summary xe2x80x93Looking for a 5-7 years experienced Data ArchitectYears of experience needed xe2x80x935-7 yearsTechnical Skills:The Hadoop Architect is responsible for designing, implementing, and maintaining large-scale, distributed data processing systems using Hadoop and related big data technologies. They oversee the architecture and design of Hadoop-based systems, ensuring scalability, security, and performance. The Hadoop Architect collaborates with data engineers, data scientists, and IT teams to deliver solutions that handle massive datasets and enable advanced analytics.Key Responsibilities:1. Architecture and System DesignHadoop System Architecture: Design, implement, and manage highly scalable Hadoop architectures tailored to specific use cases, including batch and real-time data processing.Technology Stack Selection: Choose appropriate Hadoop ecosystem tools such as HDFS, MapReduce, YARN, Hive, HBase, Pig, Oozie, Sqoop, and Flume based on business needs and data processing requirements.Scalability and Performance: Design Hadoop clusters to handle massive datasets efficiently, ensuring the system is scalable to accommodate future growth.Data Modeling: Design data models and structures to ensure optimal performance for querying, retrieval, and analytics, using both relational and NoSQL databases (HBase, Cassandra).2. Cluster Management and MonitoringCluster Configuration: Design and configure Hadoop clusters, including hardware, networking, and software installations. Optimize cluster performance by managing resource allocation, tuning configurations, and scaling nodes.Cluster Monitoring: Implement monitoring and ing systems for Hadoop clusters using tools like Ambari, Cloudera Manager, Nagios, or Ganglia to track resource usage, job performance, and system health.Security Management: Implement Hadoop security protocols, including Kerberos, SSL encryption, HDFS permissions, and data encryption to safeguard sensitive data and ensure compliance with security policies.3. Data Pipeline Development and IntegrationETL/ELT Pipelines: Collaborate with data engineering teams to build robust ETL/ELT pipelines that integrate data from diverse sources into Hadoop clusters for processing and analysis.Real-Time Data Processing: Design real-time data processing systems using technologies like Apache Kafka, Storm, or Spark Streaming for applications requiring low-latency data analysis.Data Integration: Integrate Hadoop with external databases, data warehouses, and cloud environments using tools such as Sqoop, Flume, and Nifi.4. Performance Optimization and TroubleshootingPerformance Tuning: Optimize Hadoop clusters for performance, including resource allocation, job scheduling, and tuning. MapReduce/Spark jobs.Query Optimization: Collaborate with developers to write efficient Hive, HBase, or Spark queries, improving query performance and reducing resource consumption.Troubleshooting: Diagnose and resolve complex issues in distributed systems, including job failures, resource bottlenecks, and data consistency problems.Technical Skills:Hadoop Ecosystem: Deep understanding of the Hadoop ecosystem, including HDFS, YARN, MapReduce, Hive, HBase, Pig, Oozie, Sqoop, Flume, and ZooKeeper.Distributed Computing: Proficiency in distributed computing principles, including parallel data processing, fault tolerance, and high availability.Big Data Processing Frameworks: Expertise in big data frameworks like Apache Spark, Kafka, and Storm for processing large-scale data in batch and real-time.Database Systems: Strong knowledge of SQL and NoSQL databases (e.g., HBase, Cassandra) and data warehousing technologies.Certifications Needed:NAAbout MphasisMphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis Front2Backxe2x84xa2 Transformation approach. Front2Backxe2x84xa2 uses the exponential power of cloud and cognitive to provide hyper-personalized (C=X2C2TM=1) digital experience to clients and their end customers. Mphasis Service Transformation approach helps xe2x80x98shrink the core through the application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world. Mphasis core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients.
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xe2x80x8e Equal Opportunity Employer:Mphasis is an equal opportunity/affirmative action employer. We provide equal employment opportunities to applicants and existing associates and evaluate qualified candidates without regard to race, gender, national origin, ancestry, age, color, religious creed, marital status, genetic information, sexual orientation, gender identity, gender expression, sex (including pregnancy, breast feeding and related medical conditions), mental or physical disability, medical conditions military and veteran status or any other status or condition protected by applicable federal, state, or local laws, governmental regulations and executive orders. View the EEO in the law poster , view the EEO in the law supplement . To view the pay transparency nondiscrimination provision please click and to view the E-Verify posting click .Mphasis is committed to providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of disability to search and apply for a career opportunity, please send an email to accomodationrequest@mphasis.com and let us know your contact information and the nature of your request.Skills:PRIMARY COMPETENCY : Cognitive Services PRIMARY SKILL : Big Data Processing (Apache Hadoop, Apache Spark, MySQL, NoSQL) PRIMARY SKILL PERCENTAGE : 60 SECONDARY COMPETENCY : Data Engineering SECONDARY SKILL : Data Modeler / Architect SECONDARY SKILL PERCENTAGE : 40About Company:Mphasis is a leading IT solutions provider, offering Applications, Business Process Outsourcing (BPO) and Infrastructure services globally through a combination of technology knowhow, domain and process expertise. The accolades we have been garnering can be attributed to our undeterred focus in delivering quality solutions across verticals that meet the challenging requirements of our esteemed customers. We have been recently felicitated by the economic times as the most distinguished digital company 2015. We have also been ranked 29 of 100 largest financial technology vendors by American Banker and BAI in the FinTech Forward Top 100 rankings.

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