Data Domain Architect - Associate at JPMC Candidate Experience page

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

24 May, 26

Salary

0.0

Posted On

23 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Management, Data Engineering, Data Lineage, Data Dictionaries, Data Architecture, Data Warehousing, Data Integration, Data Mart Schemas, ETL Processes, Data Pipelines, Python, Databricks, Snowflake, ThoughtSpot, Tableau, Alteryx

Industry

Financial Services

Description

Are you a skilled data professional with a passion for transforming raw data into actionable insights and a proven track record of learning and implementing new technologies? The Finance Data & Insights Team is an agile product team responsible for the development, production, and transformation of financial data and reporting across Consumer Community Banking. Our vision is to enhance the lives of our people and increase the firm's value by leveraging data and advanced tools to analyze information, generate insights, save time, improve processes and controls, and lead the organization in developing future-ready skills. As a Data Domain Architect Associate in the Consumer Community Banking - Auto Finance Data & Insights Team, you will assist in the development, testing and on-going maintenance of finance data products for the Auto Finance line of business. You will focus on understanding data requirements, developing proof of concept data against requirements, comparing data sources, testing solutions, as well as preparing ad hoc analysis for our CFO (Chief Finance Officers) stakeholders. Job Responsibilities : • Design and implement comprehensive and efficient data mart schemas that consolidate key data categories from various source systems, tailored to the needs of the Auto Finance & Business Management functions. • Collaborate with Business stakeholders to understand requirement and accordingly map source & calculation logic • Collaborate with cross-functional teams, including data engineers, data analysts, and technical specialists, to gather and analyze business requirements. • Develop, implement, and optimize data workflows, Extract Transform Load (ETL) processes, and data pipelines using Databricks. • Utilizing Databricks and ThoughtSpot tools, create a robust and efficient reporting environment for PXT Finance data analytics and reporting. • Work closely with your business domain Product teams and business stakeholders to: 1) design and develop insightful reporting and analytics solutions that drive informed decision-making; 2) apply design led thinking to meet their needs, including making data discoverable and accessible for analytical needs. • Maintain up-to-date documentation on data mart architecture, data models, ETL processes, and data governance policies. Required qualifications, capabilities and skills : • Overall 6+ years of experience in Data Management, data Engineering, data lineage, data dictionaries, and making data discoverable • Strong knowledge and experience with data Engineering, data lineage, data dictionaries, and making data discoverable • Familiarity with data architecture, data warehousing, and data integration, with a focus on the retail banking or financial services industry. • Expertise in designing and implementing scalable and efficient data mart architectures, including star schema, snowflake schema, and other data modeling techniques. • Bachelor’s degree in Computer Science, Information System, or related discipline • Experience with Python, Databricks, Snowflake, or other Cloud Data Warehouse, Data Engineering, Data Modeling, ERWIN • Proven track record of successfully managing and delivering complex data projects in a fast-paced, dynamic environment. • ThoughtSpot, Tableau, Alteryx, or Essbase experience JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

Responsibilities

The role involves designing and implementing efficient data mart schemas tailored for Auto Finance functions and collaborating with business stakeholders to map source data and calculation logic. Responsibilities also include developing, implementing, and optimizing ETL processes and data pipelines using tools like Databricks.