JPMorgan Software Engineer III - Data Engineering 

United Kingdom, England, London 

58966476

Responsibilities

• Collaborate with data scientists and research/machine learning engineers to deliver products to production.
• Build and maintain data pipelines for analytics, model evaluation and training (includes versioning, compliance and validation).
• Build and maintain scalable infrastructure as code in the cloud (private & public).
• Rapid prototyping & shorten development cycles for our software and AI/ML products:
  • Build and automate and maintain our AI/ML data pipelines & workstream from data analysis, experimentation, model training, model evaluation, deployment, operationalization, and tuning to visualization.
  • Improve and maintain our automated CI/CD pipeline while collaborating with our stakeholders, various testing partners and model contributors.
• Increase our deployment velocity, including the process for deploying models and data pipelines into production.
• Contribute to architecture and software management discussions & tasks in the overall team.

Requirements

• Minimum Bachelor of Science degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering or related field.
• Experience in Python Programming, OOP, Databases and Big Data.
• Experience in some of the following technologies Hadoop, PySpark, AWS Cloud, AWS DynamoDB, AWS Lambda, AWS Redshift, AWS Kinesis, AWS Athena, AWS Glue, Databricks, Elasticsearch, Airflow, Docker/Kubernetes/Terraform.
• 3+ years of work-related experience in professional software/data engineering role.
• Excellent problem solving and debugging skills.
• Strong interpersonal skills; able to work independently as well as in a team.
• Experience in containerization and infrastructure as code:
• Familiar with monitoring tools such as Prometheus, Grafana, Splunk and Datadog

Desirable

• You have a strong commitment to development best practices and code reviews.
• You believe in continuous learning, sharing best practices, encouraging and elevating less experienced colleagues as they learn.
• Experience with data labelling, validation, provenance and versioning.