Job Description
'Data Platforms- Architecture (Datalake on AWS, Snowflake)
Hands-on experience on AWS (AP gateway, Lambda, Glue, IAM, Lake formation, Cross account data sharing), Python, Snowflake
API, Tokenization, Encryption
Resource would be in architecture role and also required to be hands-on like building API and components based on guidance from arch team
Supporting our Chase-wide migration of data and consumers from legacy analytical data platforms to strategic data platforms
Partnering with Program, Data Platforms, data delivery, engineering teams, and data owners to modernize their data pipelines and products
Guides evaluation of current technology and leads evaluation of new technologies using existing standards and frameworks
Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
Work on proof-of-concepts for evolving data integration patterns closely working with the underlying platforms and frameworks groups. Identify new opportunities to improve data products and provide input and support to the business driving adoption
Document patterns and practices using modern approaches including cloud and event driven architectures
Drives decisions that influence data product design, application functionality, and technical operations and processes
Serves as a function-wide subject matter expert in one or more areas of functional domain such as cards, operations, lending, etc.
Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
Receiving Formal training on Data Architecture and AWS Cloud Experience
Develop and review architecture and design documentation while identifying data sources, both internal and external, and working out a plan for data management that is aligned with organizational data strategy and drive architecture governance process(es)
Act as highest-level technical expert, resolving issues, assessing any potential risks and identifying solutions across the portfolio
Designing systems for high availability, scale, and compliant data exchange with operational stability
Hands-on working experience in data processing and transformation frameworks to enable data productization development (e.g. ETL/ELT, Hadoop, Spark, Databricks, etc.)
at scale by building large scale data pipelines in batch and streamining
