Data Engineer II - AWS/PySpark/ETL

JPMorgan Chase & Co.•Columbus, OH

13h

About The Position

As a Data Engineer within JPMorgan Chase’s Consumer & Community Banking (CCB) and Data Technology team, you will serve as a member of an agile team designing and delivering trusted data collection, storage, access, and analytics solutions that are secure, stable, and scalable. As a core technical contributor, you will deliver technology solutions across multiple technical areas in support of the firm’s business objectives. The role involves developing and maintaining data pipelines, extracting and transforming data, ensuring data quality and availability, and improving operational stability and workflow automation.

Requirements

Experience with ETL tools such as Ab Initio, Informatica, or Data Pipeline, and workflow management tools such as Airflow.
Strong hands-on coding experience with PySpark, Python, and AWS.
Experience working with modern data lakes, such as Snowflake or Databricks.
Practical experience delivering system design, application development, testing, and operational stability.
Very strong problem-solving skills.
Proficiency in automation and continuous delivery methods.
Willingness and ability to learn new skillsets.

Nice To Haves

Advanced proficiency in one or more programming languages such as SQL or Java.
Proficiency across the Software Development Life Cycle.
Advanced understanding of agile methodologies, including CI/CD, application resiliency, and security.
Demonstrated proficiency in software applications and technical processes within a technical discipline such as cloud, artificial intelligence, or machine learning.
In-depth knowledge of the financial services industry and its IT systems.
Practical cloud-native experience.
Proven leadership and mentoring experience with software engineers at varying levels.

Responsibilities

Design, develop, and troubleshoot software solutions, using creative approaches to solve technical problems.
Develop secure, high-quality production code and review and debug code written by others.
Identify opportunities to eliminate or automate recurring issues to improve application and system stability.
Collaborate with cross-functional teams to develop efficient data pipelines for data-driven initiatives.
Apply data engineering best practices to ensure data quality, reliability, and performance.
Extract data and implement complex data transformations to meet business requirements.
Improve data pipelines and ensure consistent data delivery across projects.
Monitor and execute data quality checks to identify and address anomalies.
Ensure data availability and accuracy for analytical purposes.
Identify opportunities to automate data engineering workflows.
Communicate technical concepts to technical and non-technical stakeholders.

Benefits

Competitive total rewards package, including base salary determined by role, experience, skill set, and location.
Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
Comprehensive health care coverage.
On-site health and wellness centers.
Retirement savings plan.
Backup childcare.
Tuition reimbursement.
Mental health support.
Financial coaching.

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