Director of Data, Manage Team of 25 + Data/Analytic Engineer
Role and Responsibilities
Lead a Data and Analytics engineering team to create an accessible and comprehensive view of customer and product data through consolidating and rationalizing existing disparate data stores. Based on a consolidated data store build advance analytics to drive knowledge based customer interactions, enable self-service, and create intelligent product recommendations.
- Create and lead a high performing data and analytics engineering team that can drive and use Big Data to intelligently interact with its customers.
- Improve visibility to Customer interactions. For the business create product cross-selling and upselling opportunities. For our customers create personalized recommendations based on a deep understanding of who they are.
- Assess the current team and build skill in critical data engineering disciplines, such as: Data Warehouses, Business Intelligence, NoSQL, Hadoop, Storm, Kafka, Cassandra, Redshift, MapReduce, Machine Learning Techniques
- Drive agile engineering best practices and implement SAFe methodology across the teams.
- Deliver incremental capability on a regular basis, continually increasing the strength of our data and analytics portfolio.
- Recruit and develop strong engineering talent across the organization.
Qualifications and Education Requirements
Deep experience with Big Data Technologies and how to use them to help a business harness the power of it’s business and customer data. Experience leading a 25+ person Data and Analytics Engineering Team.
- Bachelor’s Degree in Engineering, Master’s Preferred, Data Oriented Preferred
- Experience in an agile engineering model and implementing high quality engineering best practices
- 15+ years of progressive experience in software product development, with a track record of successful high quality deliveries
- Experience leading and managing teams of 25+ engineers
- Ability to lead by influence and drive change in an organization
- Experience with key Big Data technologies, such as Hadoop, Storm, Kafka, NoSQL, Cassandra, Redshift, MapReduce
- Experience with Cloud Computing and Big Data and how to best leverage the two disciplines
- Ability to create an architecture and vision for how to best employ data and analytics technologies to its business needs.
- Ability to decompose that vision into manageable pieces and drive an engineering team to deliver high quality working software.
- Experience with high quality agile engineering best practices
- Experience leading BOTH development and quality functions
- Ability to identify metrics that are critical to engineering progress
- Ability to hire, train, and grow top engineering talent in the Data disciplines
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