Lead Software Engineer Data bricks, ML, Cloud

We have an opportunity to impact your career and provide an adventure where you can push the limits of whats possible.

As a Lead Software Engineer at JPMorganChase within the Corportate Sector youare an integral part of an agile team that works to enhance build and deliver trusted market-leading technology products in a secure stable and scalable way. As a core technical contributor you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firms business objectives.

Job responsibilities:

• Provide technical leadership across design development and troubleshooting for complex multi-domain solutions; establish engineering standards and best practices for the team.
• Write secure high-quality code in Python and/or Java; conduct reviews and mentor engineers to raise code quality and maintainability.
• Build and productionize cloud-based ML pipelines; drive model deployment and operationalization in collaboration with Data Science and SRE/Platform teams.
• Own MLOps workflows; coordinate infrastructure and production changes with SRE; ensure resiliency observability and security across the ML lifecycle.
• Apply SDLC tooling and automation to improve delivery velocity and reliability; champion CI/CD and cloud-native best practices.
• Partner with Product Owners and business stakeholders to translate requirements into scalable solutions aligned to CCB Finance objectives.
• Adds to team culture of diversity opportunity inclusion and respect

Required qualifications capabilities and skills:

• Formal training or certification on software engineering concepts and 5 years applied experience.
• 8 years of hands-on experience in software engineering system design application development testing and operational stability.
• Proficiency in Python and/or Java; strong grounding in secure coding practices.
• Cloud engineering experience building ML pipelines and deploying models to production with AWS services such as ECS EMR Lambda EC2 SageMaker; familiarity with TensorFlow is a plus.
• Experience with PySpark Kafka Terraform and Kubernetes for data processing streaming IaC and container orchestration.
• Database experience with Oracle and/or Cassandra; familiarity with data modeling and query optimization preferred.
• Familiarity with CI/CD application resiliency security best practices Agile/Scrum methodologies and SDLC automation tools.

• Background with machine learning frameworks MLOps practices and end-to-end ML lifecycle management (feature pipelines model registry monitoring drift detection).
• Experience with the Python ML ecosystem (pandas NumPy) and platforms such as Databricks for data engineering and model development at scale.