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 III at JPMorgan Chase within Corporate and Investment Bank Payments Technology, you serve as a seasoned member of an agile team to design and deliver trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You are responsible for developing, testing, and maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• End-to-End Data Pipeline Development:

• Own the review of controls to ensure sufficient protection of enterprise data

• Drive the Design, implementation, and maintenance of scalable data pipelines for collecting, transforming, and delivering data across systems.

• Define, maintain and update data models based on new use cases.

• Ensure data quality, reliability, and timeliness throughout the pipeline.

• Data Integration & Movement:

• Develop solutions for moving data between internal and external systems securely and efficiently.

• Work with structured and unstructured data sources.

• Analytical Insights:

• Analyze large datasets to extract actionable insights and present findings in a business-friendly format.

• Collaborate with data scientists and business stakeholders to identify opportunities for impactful analysis.

• Algorithm Support:

Provide clean, well-structured data to support predictive models and algorithms for cash forecasting and fund movement.

• Collaboration & Communication: Work closely with product, engineering, and business teams to understand requirements and deliver solutions.
• Document processes and share knowledge with team members.

Required qualifications, capabilities, and skills

• Experience in data engineering or a closely related field.
• Proven experience designing and building scalable data pipelines (ETL/ELT) for batch and streaming use cases using modern technologies (e.g., Python, SQL, Spark, Flink, Airflow) and advanced knowledge on the workings of these.
• 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 statistical analysis skills with the ability to interpret complex data, determine appropriate tooling, 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.
• Experience with financial concepts, especially in banking, treasury and cash management.
  Preferred qualifications, capabilities, and skills - Experience supporting predictive analytics or machine learning workflows.
• Knowledge of data governance, security, and compliance in financial services.
• Experience with CI/CD concepts, Git and end to end software delivery lifecycle
• Experience with OOP languages such as Java
• Exposure to front end technologies such as Java

Script and React: