Job Description :
Role Enterprise Architect
Work Location Atlanta
Duration Long term
Assignment start date 2nd week of Feb’18
Total experience in required skill (years) 10+
Desirable Technical / Functional Skills
Hadoop, MapReduce, Hive, HBase, MongoDB, Cassandra, Spark, .Impala, Oozie, , Flume, ZooKeeper, Sqoop etc, NoSQL databases.
Mandatory Technical / Functional Skills
10-15 years of working experience with 3+ years of experience as Big Data solutions architect. Needs to have
experience with the major big data solutions like Hadoop, MapReduce, Hive, HBase, MongoDB, Cassandra, Spark, .Impala, Oozie, , Flume, ZooKeeper, Sqoop etc, NoSQL databases.
Big Data Solution Architect Certified Preferred.
Big Data Certification is a must.
Work experience on various distributions such as Cloudera, Hortonworks, MapR etc.
Propose best practices/standards with data security and privacy handling experience.
Knowledge in handling different kinds of source systems and different formats of data.
Hands-on experience with Hadoop applications (e.g. administration, configuration management, monitoring, debugging, and performance tuning
Strong knowledge of major programming/scripting languages like Java, Linux, R, Scala etc. As well as have experience in working with ETL tools such as Informatica, Talend and/or Pentaho.
Experience in designing multiple data lake solutions with a good understanding of cluster and parallel architecture.
Experience Cloud Computing.
To be able to benchmark systems, analyze system bottlenecks and propose solutions to eliminate them.
To be able to clearly articulate pros and cons of various technologies and platforms.
Ability to consistently drive self and others to achieve results despite obstacles and setbacks.
Must possess strong oral / written communication and listening skills.
To be able to perform detailed analysis of business problems and technical environments and use this in designing the solution.
To be able to work in a fast-paced agile development environment.
Ability to achieve results with a hands-on, collaborative approach; works well in a team.
Proficient in encouraging diverse thinking to promote and nurture innovation.
Demonstrated ability to align career development goals with organizational objectives.
Ability to understand customers’ need and concerns and be able to customize services and products as appropriate.
Ability to regularly learn and adopt new technology.
Strong understanding of relational database structures, theories, principles, and practices.
Hands-on experience with data architecting, data mining, large-scale data modeling, and business requirements gathering/analysis.
Familiarity with in-house data-intensive applications, including enterprise Business Intelligence and Reporting tools.
In-depth technical knowledge of network, PC, and platform operating systems
Working technical knowledge of current systems software, protocols, and standards
Experience with data processing flowcharting techniques.
Proven project management experience.
Strong understanding of the organization’s goals and objectives.
Good knowledge of applicable data privacy practices and laws.Strong understanding of end-user needs and requirements.
Attention to detail and strong analytical skills.
Ability to multi-task, prioritize issues and monitor progress.
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job.
Able to communicate with others by telephone and in person.
Able to utilize a computer for word processing, email communication, and preparation of documents and presentations.
May require sitting for extended periods of time.
Roles and responsibility
In partnership with senior and executive leadership, establishes overall vision and creates a culture that treats data as an asset.
Develop conceptual, logical, and physical models for enterprise analytic applications, integrations, master data, and transactional applications.
Partner with Data Services team to ensure that data models and data are properly cataloged in our enterprise data dictionary.
Work in collaboration with BI and application development to strategize and execute on target data architecture, standardize and manage key dimensions.
Define standards on best approaches and techniques for transporting data real-time and near real-time.
Ability to communicate at all levels with both business and technology leaders, with a strong understand of business data requirements and technology capabilities.
Provide strategic direction and oversee the integration of Big Data platforms and tools for advanced analytics including machine learning/data science that drive business value.
Plan and implement capacity and resource expansion to ensure data store scalability. Define data purge and archive processes/standards to ensure appropriate data maintenenace is performed.
Design and implement redundant systems, policies, and procedures for disaster recovery and data archiving to ensure effective availability, protection, and integrity of data assets.
Conduct research and make recommendations on data products, services, protocols, and standards in support of procurement and development efforts.
Evaluate, recommend, and select data warehouse components, including hardware, database management systems, ETL (extract, transform, load) software, data mining tools, and meta data management tools.
Create models for new data warehouse development and/or changes to existing data stores.
Perform cost estimates for data migration between development, test, and production systems, and plan and coordinate these migrations.
Develop, implement, and maintain change control and testing processes for modifications to data systems.
Mentor and/or provide leadership to junior members of the IT team.
Desirable Technical / Functional Skills
Hadoop, MapReduce, Hive, HBase, MongoDB, Cassandra, Spark, .Impala, Oozie, , Flume, ZooKeeper, Sqoop etc, NoSQL databases.