Data Engineer III

We are building the next generation of digital banking and data platforms, and you will play a key role in shaping how data powers critical business decisions. As a Data Engineer, you will work within an agile, collaborative team to design and deliver scalable, secure, and high-quality data solutions. You will help drive innovation by building resilient data systems that support analytics, insights, and customer-focused products.

As a Data Engineer III at JPMorgan Chase within the International Consumer Bank, you will design, build, and maintain scalable data platforms and pipelines on cloud infrastructure. You will partner with engineering, analytics, and business teams to ensure data is reliable, accessible, and actionable. This role requires strong engineering fundamentals, hands-on coding experience, and a passion for building modern, cloud-native data solutions.

Job responsibilities:

• Build and maintain scalable data pipelines and architectures on cloud platforms, primarily AWS
• Develop, test, and deploy high-quality data and backend solutions with a focus on reliability and performance
• Design and implement microservices and APIs to support data workflows and integrations
• Optimize data processing systems to handle large-scale datasets efficiently and ensure high availability
• Implement data solutions using distributed processing frameworks such as Spark or PySpark
• Apply Agile and DevOps practices, including CI/CD, automation, and infrastructure as code
• Collaborate with stakeholders to understand data requirements and improve data accessibility and usability
• Ensure data quality, integrity, and consistency across systems and platforms
• Support integration of data into analytics and reporting platforms for business insights
• Contribute to building resilient, secure, and scalable systems aligned with engineering best practices

• Bachelor's degree in Computer Science, Engineering, or a related discipline
• Hands-on experience in data engineering or backend software engineering
• Strong programming skills in Python with experience in data processing frameworks such as Spark or PySpark
• Experience building and maintaining data pipelines and large-scale data systems (data lake or warehouse environments)
• Knowledge of SQL and experience working with structured and unstructured datasets
• Experience with distributed systems and scalable data architectures
• Familiarity with CI/CD practices, Agile methodologies, and application resiliency
• Experience with data tools such as dbt, Glue, or Trino
• Exposure to orchestration tools such as Airflow or Step Functions and experience with infrastructure as code

• Experience with containerization technologies such as Docker and Kubernetes
• Understanding of cloud platforms, preferably AWS
• Knowledge of streaming and real-time data processing (Kafka, Spark Streaming)
• Experience building automated testing frameworks across unit, integration, and end-to-end levels
• Exposure to modern frontend technologies such as TypeScript or React
• Cloud certifications in AWS (e.g., Data Engineer or Solutions Architect)