Experience/ Qualifications | - Minimum of 10+ years of total experience
- Minimum of 7+ years as data/hadoop architect
- Hands on experience in Big Data space (Hadoop Stack like M/R, HDFS, Pig, Hive, HBase, Flume, Sqoop, etc. NoSQL stores like Cassandra, HBase etc.). Work closely with product management and development team to understand functional requirements and propose architecture, NFRs, develop proof of concept to validate technical unknowns.
- Expertise in building massively scalable distributed data processing solutions with Hadoop, Hive & Pig Proficiency with Big Data processing technologies (Hadoop, HBase, Flume, Oozie)
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Responsibilities | - To conceptualize, design and deliver solution delivery through the team as per defined scope and standards in a particular technology related to databases
- To define practices to manage data at rest and as data moves through the enterprise, coordinating the efforts of the various teams involved
- To develop, analyse, and maintain the data architecture
- To serve as a subject matter expert and perform tasks that contribute to and define the organizations mission and vision
- To improve and streamline data practices and assist in defining interfaces, improving the organizations understanding of data and access to data across the enterprise
- To provide leadership and guidance to the organization in regard to enterprise data strategies, such as data quality, data flows, data warehousing, big data, data analytics, and data science
- Deep experience with distributed systems, large scale non-relational data stores, map-reduce systems, data modeling, database performance, and multi-terabyte data warehouses
- To define technical standards and guidelines related to data flows and data consumption
- To document databases, interfaces, data movement, and mapping data sources/data stores
- To create and revise data dictionary definitions, data governance practices, and data standards
- To define quality of service requirements: data currency, availability, response times and data volume
- To partner with the architecture team to ensure compliance with data security, privacy mandates, enterprise architecture standards
- To educate peers and cross-train team members in relation to data management strategies, data warehousing, data flows, and data architecture
- To troubleshoot problems and questions pertaining to system applications, interfaces and data integration as needed
- To evaluate and recommend new and emerging data management and data storage technologies and data architecture standards
- To ensure consistency between data management, enterprise storage and all other technical system components
- To remain current with emerging data technologies, best practices, and industry trends.
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