1. Strong foundation for compute architecture, parallel processing and data engineering
2. Proven track record of delivering business value through innovative solutions
3. Industry and peer recognition in the field of data and analytics
4. Proven track record of communicating and delivering value to the C-suite of enterprise
5. Strong Experience with RDBMS, Data Warehousing, SQL, and information modeling
6. Knowledge of Data Integration framework and methodologies
7. Good understanding of Data Quality and Governance in an enterprise setting
8. Understanding of statistical analysis and applied mathematics, experience with statistical and predictive modeling analysis tools such as Revolution R
9. Hands on experience developing in SQL, Python, Hive, Pig and architecting Hadoop ecosystems.
10. Ability to communicate complex analysis in a clear, precise, actionable manner.
11. Successful experience driving projects to completion with minimal guidance and ability to integrate tightly with various business and operations functions internally.
12. Track record of success in oneor more of these areas:data quality, machine learning, big data architecture, predictive analysis, NLP (Natural Language Processing), information governance etc.