Data Engineer

Job Description

You thrive on diversity and creativity, and we welcome individuals who share our vision of making a lasting impact. Your unique combination of design thinking and experience will help us achieve new heights.

As a Data Engineer II at JPMorgan Chase within the CCB , you are part of an agile team that works to enhance, design, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable manner. As an emerging member of a data engineering team, you execute data solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.

Job Responsibilities

• Design, develop, and maintain scalable data pipelines using PySpark, AWS and Snowflake to support platform modernization and data delivery goals.
• Contribute to the exit of legacy platforms (HWX and ABINITIO) by migrating data products and processes to modern cloud-based solutions.
• Collaborate with cross-functional teams to deliver product and D&A (Data & Analytics) deliverables, ensuring alignment with business objectives.
• Optimize ETL processes and drive operational excellence by implementing best practices in data engineering and automation.
• Enhance productivity for BOW and RTB initiatives through innovative data solutions and teamwork.
• Ensure robust risk & controls in all data delivery activities, maintaining compliance and data integrity.
• Demonstrate leadership and teamwork in driving data delivery projects, fostering a culture of collaboration and continuous improvement.
• Produce architecture and design artifacts for data applications, ensuring design constraints are met and solutions are scalable.
• Analyze, synthesize, and visualize data from diverse sources to support decision-making and continuous improvement.
• Identify hidden problems and patterns in data to drive improvements in coding hygiene, system architecture, and operational processes.
  
  

Required Qualifications, Capabilities, And Skills

• Experience in data engineering or a closely related field.
• Proven experience designing and building scalable data pipelines (HWX and ABINITIO) for batch and streaming use cases using modern technologies (e.g., Python, SQL, Spark, Flink, Airflow)
• Hands-on experience in building and operating workloads Databricks.
• Hands-on experience creating data visualizations and dashboards in Tableau.
• Familiarity with cloud data platforms (e.g., AWS, Azure, GCP) and big data technologies.
• Strong analytical skills with the ability to interpret complex data, build performant datasets, and deliver business value.
• Experience integrating data from multiple sources and systems (APIs, databases, files, streaming), including data modeling and orchestration best practices.
• Ability to work independently and collaboratively in a fast-paced, agile environment, partnering with data scientists, analysts, software engineers and business stakeholders.
• Excellent communication and documentation skills, including clear articulation of data designs, lineage, and assumptions for technical and non-technical audiences.
  
  

Preferred Qualifications, Capabilities, And Skills

• Awareness or experience with financial concepts, especially in banking, treasury and cash management.
• Experience supporting predictive analytics or machine learning workflows.
• Knowledge of data governance, security, and compliance in financial services.
• Familiarity with CI/CD concepts, Git and end to end software delivery lifecycle
• Familiarity with OOP languages such as Java
• Exposure to front end technologies such as Javascript and React