Data Engineer III

Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.

As a Data Engineer III at JPMorgan Chase within the International Consumer Bank, 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

1. Develop and implement processes and procedures to identify, monitor, and mitigate data risks within the product.
2. Design and implement complex, scalable solutions to efficiently process data, ensuring consistent and timely delivery and availability.
3. Focus on building robust systems that can handle large volumes of data with minimal downtime.
4. Develop solutions using Agile DevOps methodologies and continuous integration/continuous deployment (CI/CD) practices on public cloud platforms.
5. Create reusable frameworks with a strong emphasis on quality and long-term sustainability.
6. Collaborate with key partners to enhance understanding of data usage within the business.
7. Serve as a subject matter expert on the content and application of data in the product and related business areas.
8. Support the Data Analytics & Insight team by identifying and integrating necessary data into analytics platforms.
9. Document and enforce requirements for data accuracy, completeness, and timeliness within the product.
10. Contribute to a team culture that values diversity, equity, inclusion, and respect.

1. Bachelor's degree in Computer Science, Engineering, Information Systems, or related disciplines.
2. Minimum 3 years of experience in data engineering.
3. Working understanding of NoSQL databases.
4. Professional experience in an agile, dynamic, and customer-facing environment.
5. Recent hands-on experience actively coding as a data engineer (back-end software engineer considered).
6. Understanding of distributed systems and cloud technologies (AWS, GCP, Azure, etc.).
7. Understanding of data streaming and scalable data processing frameworks (Kafka, Spark Structured Streaming, Flink, Beam, etc.).
8. Experience with SQL (any dialect) and data tools (e.g., Dbt, Glue).
9. Experience in all stages of the software development lifecycle (requirements, design, architecture, development, testing, deployment, release, and support).
10. Experience with large-scale datasets, data lake, and data warehouse technologies on at least TB scale (ideally PB scale) with Redshift, Snowflake, or BigQuery.
11. Experience in Infrastructure as Code (ideally Terraform) for cloud-based data infrastructure and extensive knowledge of Python or good experience with a JVM language.

1. Experience with a scheduling system (Airflow etc.).
2. Understanding of (distributed and non-distributed) data structures, caching concepts, CAP theorem.
3. Understanding of security frameworks / standards and privacy.
4. Experience in automating deployment, releases and testing in continuous integration, continuous delivery pipelines is desired.
5. A solid approach to writing unit level tests using mocking frameworks, as well as automating component, integration and end-to-end tests.
6. Experience with containers and container-based deployment environment (Docker, Kubernetes, etc.).