VP Leadership Hiring at JP Morgan Chase
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JP Morgan Chase - Executive Director - Data Infrastructure & Governance (15-18 yrs)
Executive Director Data Infrastructure & Governance
- CCB is the U.S. Consumer and Community Banking business of JPMorgan Chase & Co. (NYSE: JPM), a leading global financial services firm with assets of $2.5 trillion and operations worldwide. Chase serves nearly half of America's households with a broad range of financial services, including business banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. Consumer and Business customers can choose how and where they want to bank: 5,200 branches, 16,000 ATMs, mobile, online and by phone. For more information, go to Chase.com.
- This role is responsible for leading the India based team of Business Data Architects, Data Stewards and Data quality professionals within the CCB Data & Analytics function. Business Data Architects within the CCB Data Infrastructure focus on Data Management and supporting our Analytics Partners.
- They work with agile development patterns, supporting migration of legacy and processes and data from Business Analysts and Data Science Teams to Technology Supported Platforms and Operations. They need to be the bridge between Data Scientists and Technology Production and Operations - taking data and processes from current state to Target state
- The candidate must exhibit a thorough understanding of data structures, data manipulation, metadata, data security, data stewardship and data quality management. In addition, the candidate must have a solid understanding of CCB businesses, functions, systems, data environments, and processes that are necessary for the production and utilization of customer data.
- The candidate must have the ability to partner with stakeholders globally inside and outside of the department to understand their needs and support the design and development of robust data solutions that meet and/or exceed customer expectations. The ideal candidate will possess JPM institutional data and system knowledge, technical skills, an understanding of data science, and a commitment to producing high quality results. Experience with leading teams delivering
- The candidate must have an educational background in Computer Science, MIS, Software Engineering, or a related discipline. In addition, the candidate must have a minimum of a Bachelor's degree or a Master's degree with 15+ years of experience
- 15+ years working with Data Management discipline including understanding of data infrastructure and data governance toolkit
- Strong experience in Hadoop big data environments using MapReduce, Hive, SparkSQL, Sqoop, HDFS, and Spark
- Experience in one of Big Data Consumption OLAP tools (AtScale, Kyvos or other OLAP on Hadoop).
- Being meticulous about tracking things and follow-through.
- Work with customers on how to use the AtScale Design Center for modeling solutions
- BI Experience a must (Tableau, Cognos, Qlik, BO, SSAS)
- Java, Scala, Python, Shell Scripting a plus
- 8+ years of Professional Services (customer facing) experience architecting large scale storage, data center and /or globally distributed solutions
- Experience in Hadoop related tools and technologies is a must (HDFS and/or MapReduce, HBase, Hive, Spark, Impala)
- Technical understanding of common RDBMS systems; (e.g. Teradata, Oracle)
- Understanding of Hadoop-related technologies & their applications
- Must have ability to deliver high-quality results under tight deadlines and be comfortable managing large projects
- Must have strong people management experience and ability to manage diverse, multi-talented team across locations
- Strong skills in project management methodologies and tools - Agile Training and certification a plus.
- Advanced analytical thinking and problem solving skills
- Proven experience with data infrastructure initiatives, best practices and key components
- Proven expertise in Data Governance and Data quality discipline
- Knowledge of the business lending, card and deposit lifecycle, including origination, sale/servicing, default management/loss mitigation and fraud.
- Ability to Create conceptual & logical models to describe a particular domain of data and use these models to inform the physical design of data-related projects