As a Data Engineer II, you will design and maintain data solutions, optimize data workflows, implement ETL processes, and ensure data integrity in a collaborative team environment.
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 Asset & Wealth Management, you are part of an agile team that works to enhance, design, and deliver the data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. 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
Required qualifications, capabilities, and skills
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 Asset & Wealth Management, you are part of an agile team that works to enhance, design, and deliver the data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. 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
- Designs, develop, and maintain scalable data pipelines on AWS using services such as Glue, EMR, Lambda, and Redshift.
- Collaborates with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions.
- Implements ETL processes to ingest, transform, and load data from various sources into cloud-based data warehouses.
- Optimizes data workflows for performance, reliability, and cost efficiency.
- Ensures data quality, integrity, and security across all stages of the data lifecycle.
- Monitors, troubleshoot, and resolve issues in production data pipelines.
- Documents data architecture, processes, and best practices for team knowledge sharing.
Required qualifications, capabilities, and skills
- Formal training or certification on data engineering concepts and 2+ years applied experience
- Experience in data engineering, with a focus on cloud-based solutions (AWS).
- Strong proficiency in SQL and Python.
- Experience with building and managing ETL pipelines.
- Familiarity with data modeling, warehousing concepts, and big data technologies.
- Knowledge of data governance, security, and compliance best practices.
- Excellent problem-solving skills and ability to work independently or in a team environment.
- Strong communication skills for technical and non-technical audiences.
- Tools : AWS Glue, AWS Lambda, AWS EMR, AWS Redshift, Amazon S3, Pub/Sub Services: Amazon SNS, SQS, MSK, Apache Spark, Apache Airflow, Python, SQL, Git, CI/CD tools (e.g., Jenkins, AWS CodePipeline), Monitoring tools (e.g., CloudWatch, Datadog)
Top Skills
Amazon S3
Apache Airflow
Spark
Aws Codepipeline
Aws Emr
Aws Glue
Aws Lambda
Aws Redshift
Cloudwatch
Datadog
Git
Jenkins
Python
SQL
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