Wholesale Credit RiskAssociate - Product Strategy

Aumni; Mumbai; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

JPMorganChase in Mumbai seeks a Data/AI Engineer to build robust data foundations and scalable pipelines across platforms. You will own end-to-end delivery, apply business rules, and deliver comprehensive datasets for end-user consumption with SQL and Python.

You will lead data modeling, metadata strategies, and generative AI workflows, delivering demos to stakeholders and ensuring cross-platform data consistency.

Qualifications

• Master's or Bachelor's in CS/IT/Data Eng with experience or equivalent.
• Proficient in Python with Pandas and NumPy for ETL pipelines.
• Strong SQL skills including window functions and procedures.
• Experience creating Tableau dashboards and reports.
• Exposure to AWS, Databricks and PySpark for data processing.
• Experience with generative AI pipelines and LangChain or similar.
• Knowledge of vector databases and embedding models.
• Proven ability to lead development and stakeholder communication.

Responsibilities

• Develop frameworks to extract data from multiple sources and deliver datasets.
• Ensure cross-platform data consistency and perform gap analysis.
• Create analytics and visualizations including dashboards in Tableau.
• Own end-to-end SDLC activities: requirements, design, development, testing, deployment.
• Define data models, metadata, and dictionaries for analysis.
• Perform UAT and deliver stakeholder demos using SQL and Python.
• Identify data problems and improve data pipelines and architecture.
• Build scalable pipelines using Databricks and PySpark.
• Design end-to-end generative AI pipelines for LLM-powered apps.
• Incorporate prompt engineering and vector storage for retrieval-based systems.
• Lead development with regular stakeholder meetings and guidance to juniors.

Skills

Python with Pandas NumPy

SQL (window functions, stored procs)

Tableau dashboards

ETL pipelines

AWS Databricks PySpark

LangChain LlamaIndex Transformers

vector databases (Pinecone ChromaDB FA

Education

Master's in CS/IT/Data Eng or related + 2 yrs exp

Bachelor's in same fields + 2 yrs exp

Tools

Oracle PL/SQL

Microsoft SQL Server

Python

Tableau

Databricks

PySpark

Job description

Build robust data foundations that power analytics and intelligent applications. You will develop scalable pipelines and consistent datasets across platforms, turning complex data into clear insights and visualizations. You will own delivery end-to-end across the software development life cycle, from requirements through support. You will partner closely with stakeholders, perform user acceptance testing, and deliver demos using SQL and Python.

As a Data/AI Engineer, you will develop robust frameworks to extract data from multiple sources, apply business rules, and deliver comprehensive datasets for end-user consumption. You will ensure cross-platform data consistency and perform gap analysis using advanced software technologies. You will conduct data exploration, analytics, and visualization to support analysis and exploration of large datasets. You will own all phases of the software development life cycle, including requirements gathering, design, development, testing, implementation, and support, with a focus on data models, metadata, and business transformation strategies. You will perform user acceptance testing and deliver demos to stakeholders using SQL queries and Python scripts.

Job responsibilities

• Develop frameworks to extract data from multiple sources, apply business rules, and deliver comprehensive datasets for end-user consumption.
• Ensure cross-platform data consistency and perform gap analysis using advanced software technologies.
• Explore data and deliver analytics and visualizations, including insightful dashboards and reports in Tableau.
• Own end-to-end software development life cycle activities: requirements gathering, design, development, testing, implementation, and support.
• Define data models, metadata, and data dictionaries to enable thorough analysis and analytical explorations.
• Perform user acceptance testing and deliver stakeholder demos using SQL queries and Python scripts.
• Identify hidden data problems and patterns and drive improvements in coding hygiene and system architecture.
• Build and optimize scalable data pipelines, leveraging tools such as Databricks and PySpark for processing and analysis.
• Design and build end-to-end generative AI pipelines, including ingestion, preprocessing, model integration, and deployment workflows for large language model-powered applications.
• Incorporate prompt engineering and vector storage to enable intelligent, context-aware retrieval and response generation.
• Lead development activities by conducting regular stakeholder meetings, communicating timelines and blockers, and providing guidance to junior engineers and technologists.

Required qualifications, capabilities, and skills

• Education/experience: Master's degree in Computer Science, Information Technology, Data Engineering, or related field; or Bachelor's degree in the same fields plus 2 years of experience in the job offered or a similar technical role.
• Python proficiency, including Pandas and NumPy, with demonstrated experience developing and optimizing extract, transform, load (ETL) pipelines for data migration and processing.
• SQL proficiency, including window functions and creating stored procedures.
• Experience with Tableau to create dashboards and reports for analytics and visualization.
• Strong grounding in data engineering concepts, including ETL processes, data pipeline optimization, and data migration strategies.
• Experience with Oracle PL/SQL and Microsoft SQL Server for data management and analysis.
• Experience with AWS, Databricks, and PySpark for data processing and analysis.
• Experience building and optimizing end-to-end generative AI pipelines, including data preprocessing, large language model integration, prompt engineering, and deployment workflows using LangChain, LlamaIndex, or Hugging Face Transformers.
• Experience with retrieval-augmented generation architecture, including vector databases (Pinecone, ChromaDB, FAISS) and embedding models for context-aware retrieval systems.
• Experience leading development activities, conducting stakeholder meetings, and communicating timelines and blockers.

Preferred qualifications, capabilities, and skills

• Experience performing statistical analysis to interpret data, identify trends, and draw conclusions using scikit-learn and TensorFlow.
• Experience designing and managing scalable data pipelines using Airflow, Linux, and Git.
• Experience improving pipeline performance using parallelism, multi-threading, and batch processing techniques.

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. 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.

J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. Build scalable data pipelines and trusted datasets in Databricks, delivering Tableau insights and stakeholder-ready demos.