Data Engineer III - Python Java
Data Engineer III - Python Java
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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 III at JPMorgan Chase within the Payments Trust & Safety team 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. Our goal is to keep JPMorgan Chase and our clients safe as they transact through ACH Wire and Credit card channels. The Data team is responsible to make largescale data across lines of Business for applying machinelearning to our most critical and widerange customer products to solve not only Trust & Safety problems (e.g. Fraud) but also related problems (e.g. payment optimization forecasting). As a member of this team you will work with many lines of business and develop Machine Learning solutions that have a broader impact for the bank. We work closely with our engineering and product partners to develop and deploy solutions to reach our customers.
Job Responsibilities:
- Collaborate with all of JPMorgans lines of business and functions to delivery software solutions.
- Experiment Architect develop and productionize efficient Data pipelines Data services and Data platforms contributing to the Business.
- Design and implement highly scalable efficient and reliable data processing pipelines and perform analysis and insights to drive and optimize business result.
- Acts on previously identified opportunities toconvergephysical IT and datasecurityarchitecture to manageaccess
- Champions the firms culture of diversity equity inclusion and respect
Required qualifications capabilities and skills:
- Formal training or certification on large scale technology program concepts and 3 years applied experience in Data Technologies.
- Experienced programming skills with Java and Python.
- Experience across the data lifecycle building Data frameworks working with Data lakes.
- Experience with Batch and Real time Data processing with Spark or Flink
- Working knowledge of AWS Glue and EMR usage for Data processing
- Experience working with Databricks
- Experience working with Python/Java PySpark etc.
- Working experience with bothrelational and NoSQL databases
- Experience in ETL data pipelines both batch and realtime data processing Data warehousing NoSQL DB.
Preferred qualifications capabilities and skills :
- Cloud computing: Amazon Web Service Docker Kubernetes.
- Experience in big data technologies: Hadoop Hive Spark Kafka.
- Experience in distributed system design and development
Employment Type
Full-Time
