DescriptionYou 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 youare 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 ondata engineeringconcepts 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)
DescriptionYou 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 youare...
DescriptionYou 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 youare 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 ondata engineeringconcepts 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)
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