What are the responsibilities and job description for the Data Platforms- Data Domain Architect Senior Associate position at JPMorgan Chase?
Join a team where you will be a data champion where you will collaborate with business analysts and engineering teams to understand requirements, prioritize the product backlog, and solve problems throughout the development lifecycle.
As a Data Domain Architect Senior Associate, within the data platform team, you will work closely with the Product Manager to deliver enterprise-class, scalable, and resilient data platforms and focus on user consumption services supporting various modes such as batch and asynchronous processing.
Job Responsibilities:
- Engage with users to understand business data usage and potential improvements. and establish and manage relationships with the analyst community.
- Impact product strategy and priorities using technical expertise. and demonstrate intellectual curiosity in solving complex business problems.
- Define features and capabilities for future user consumption services. and address disparate business needs with strong problem-solving and client engagement skills.
- Translate business needs into stories for valuable outcomes. and adapt quickly to evolving client guidance while maintaining product objectives.
- Collaborate with engineering teams to build scalable and resilient data warehouses across cloud analytic environments and leverage internal resources to deliver optimal solutions.
- Maintain and refine product backlog through agile practices and serve as a liaison between product, engineering, and architecture teams to identify design approaches.
- Validate delivered features against business requirements through testing and develop and maintain documentation to ensure data consistency and quality.
Required qualifications, capabilities, and skills:
- 3 years of experience with a strong technology background and communication skills; Educational or on-the-job experience in a technical field (e.g., Computer Science, Engineering).
- Solid understanding of SQL, Python, and other data engineering tools and familiarity with data modeling, dimensional models, and semantic layers.
Flexibility and creativity in problem-solving and analytical skills.
- Understanding of data platform technologies, including Snowflake, AWS Data Lake, and Info1.