Push the limits of what’s possible with us as an experienced member of our Software Engineering team.

As Data Engineer III - Big Data/Java/Python at JPMorgan Chase, you will join the Financial Planning and Analysis (FP & A) team to design and implement the next generation buildout of a cloud native, Driver based FP & A platform for JPMC. The FP & A organization aims to provide comprehensive solutions to managing the firm’s planning, forecasting & budgeting. The program will include strategic buildout of systematic sourcing (data lake), driver-based forecasting models and AI first approach to bring digital first reporting capabilities. The target platform must process 40-60 million transactions and positions daily, calculate forecasts as well provide a slice & dice model to provide users with a multidimensional picture of plans, forecast & budget.

Job Responsibilities:

• Design, develop, and maintain scalable data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
• Implement data mining techniques to extract valuable insights from complex data sets.
• Build and optimize data architectures using big data tools and frameworks (e.g., databricks, Spark, Python).
• Ensure data quality, integrity, and security throughout the data lifecycle.
• Collaborate with cross-functional teams to understand data requirements and deliver solutions that meet business needs.
• Monitor and troubleshoot data pipeline performance and resolve issues as they arise.
• Document data processes, workflows, and best practices.

Required Qualifications, Capabilities, and Skills

• Formal training or certification on software engineering concepts and 3+ years applied experience
• Strong hands-on development experience and in-depth knowledge of Java, Python, Spark, Data bricks & Bigdata related technologies
• Proven experience in building and maintaining data pipelines and ETL processes.
• Strong understanding of infrastructure using terraform.
• Proficiency in SQL and experience with relational and NoSQL databases.
• Experience with data mining, data wrangling, and data transformation techniques.
• Knowledge of data modeling, data warehousing, and data governance best practices.
• Strong problem-solving skills and attention to detail.
• Strong skills on OLAP (cube like) systems. Eg Atoti.
• Excellent communication and collaboration skills.

Preferred Qualifications, Capabilities, and Skills:

• Experience of working in big data solutions with evidence of ability to analyze data to drive solutions
• Familiarity with cloud platforms (e.g., AWS) and their big data services is a plus.