Big Data Cloud Architect

Description: Our Client's Analytics & Insights (A&I) Services helps organizations to provide insights that enable smart decisions across functions. A&I help organizations in data estate modernizations, in the design of innovative solutions for superior business outcomes and help execute effective data-driven strategies. They help organizations analyze their operational, business, and external data to gain insights, enabling them to be more agile and responsive to the market A&I Data Service help to create data-driven organizations by providing the right solutions in Big Data technologies, Master Data Management, Business Intelligence Analytics by taking advantage of the Cloud based computing and storage. The expansive Data Management Framework and agile centric methodology, underpins the above solutions by providing the foundations required to realize the solutions successfully. The Big Data Cloud Solution Architect will be responsible for guiding the full lifecycle of a Big Data solution, including requirements analysis, platform selection, technical architecture design, application design and development, testing, and Test and Deployment in Cloud Infrastructures. We are looking for candidates with a broad set of technology skills to be able to design and build robust Big Data solutions for big data problems and learn quickly as the platform grows Responsibilities: Provide advisory and thought leadership on the provision of analytics environments leveraging Cloud based platforms, big data technologies, including integration with existing data and analytics platforms and tools. Design and implement scalable data architectures leveraging Hadoop, NoSQL and emerging technologies, covering on-premise and cloud-based deployment patterns. Define, design and implement data access patterns for multiple analytical and operational workloads, across on-premise and Cloud based platforms Create information solutions covering data security, data privacy, metadata management, multi-tenancy and mixed workload management across Hadoop and NoSQL platforms, spanning on-premise and Cloud based deployments Delivery of customer Cloud Strategies, aligned with customer's business objectives and with a focus on Cloud Migrations ensuring global to local regulations, security, risk and compliance Qualifications: 5 years hands-on experience with the Big Data stack (HDFS, SPARK, MapReduce, Hadoop, Sqoop, Pig, Hive, Hbase, Flume, Kafka) 5 years hands-on experience with the No-SQL (e.g. MongoDB, HBase, Cassandra) 5 years hands-on experience with related/complementary open source software platforms and languages (e.g. Java, Linux, Apache, Perl/Python/PHP, Chef, Scala) 5 years of experience working on cloud platforms - Pivotal Cloud Foundry and Public Cloud AWS/Azure/Google Cloud Hands-on experience with ETL (Extract-Transform-Load) tools (e.g. Informatica, Talend, Pentaho) Knowledge / Hands-on experience with BI tools and reporting software (e.g. Microstrategy, Cognos, Pentaho) Hands-on experience with analytical tools, languages, or libraries (e.g. SAS, SPSS, R, Mahout, MLLib) Hands-on experience with "productionalizing" Big Data applications (e.g. administration, configuration management, monitoring, debugging, and performance tuning) Hadoop platforms & distributions: Cloudera, Hortonworks, MapR, EMR Previous experience with high-scale or distributed RDBMS (Teradata, Netezza, Greenplum, Aster Data, Vertica, DB2, Oracle) Proficient understanding of Underlying infrastructure for Big Data Solutions (Clustered/Distributed Computing, Storage, Data Center Networking) Strong understanding across Cloud and infrastructure components (server, storage, network, data, and applications) to deliver end to end Cloud Infrastructure architectures and designs. Knowledge of further Cloud technologies (Redshift, S3, EC2, EMR, Talend/Pentaho/Snowflake) Track record of thought leadership and innovation around Big Data. Solid understanding of Cloud Computing Technologies and related emerging technology (e.g. Amazon Web Services EC2, Elastic MapReduce, Azure, GCP) and considerations for scalable, distributed systems Knowledge of NoSQL platforms (e.g. key-value stores, graph databases, RDF triple stores)