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.
- 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.
- 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. 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.
Skills Required
- Master's degree in Computer Science, Information Technology, Data Engineering, or a related field; or bachelor's degree in these fields plus two years of relevant experience.
- Python proficiency, including Pandas and NumPy, with experience developing and optimizing ETL pipelines.
- SQL proficiency, including window functions and stored procedures.
- Experience creating Tableau dashboards and reports.
- Strong knowledge of data engineering, ETL, pipeline optimization, and data migration strategies.
- Experience with Oracle PL/SQL and Microsoft SQL Server.
- Experience with AWS, Databricks, and PySpark.
- Experience building and optimizing generative AI pipelines using data preprocessing, large language model integration, prompt engineering, and deployment workflows.
- Experience with LangChain, LlamaIndex, or Hugging Face Transformers.
- Experience with retrieval-augmented generation, vector databases such as Pinecone, ChromaDB, or FAISS, and embedding models.
- Experience leading development activities, conducting stakeholder meetings, and communicating timelines and blockers.
- Experience with statistical analysis using scikit-learn and TensorFlow.
- Experience designing and managing scalable data pipelines using Airflow, Linux, and Git.
- Experience improving pipeline performance through parallelism, multithreading, and batch processing.
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Health coverage is considered comprehensive, including medical, dental, and vision, alongside wellness and mental health resources. Some locations add onsite health centers and related wellbeing support.
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Retirement Support — Retirement offerings include a 401(k)-type savings plan and related financial benefits, with options such as employee stock purchase participation. Financial planning resources are also highlighted to support long-term savings.
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Parental & Family Support — Paid parental leave of 16 weeks for birth or adoption is available for all parents. Child care and back-up child care resources further reinforce family support.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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