What are the responsibilities and job description for the Senior Lead Software Engineer - Mainframe System Performance position at JPMorgan Chase?
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As a Senior Lead Software Engineer at JPMorgan Chase within the Mainframe System Performance team, you will be responsible for ensuring the reliability, scalability, and performance of mainframe and mid-range computing platforms. This role combines data engineering and site reliability engineering (SRE) principles to analyze and interpret large datasets, develop predictive models, and optimize system performance. You will focus on data-promoten strategies to enhance automated processes, streamline operations, and support full stack application development.
Job responsibilities:
- Automate repetitive tasks related to deployments, monitoring, and incident response.
- Implement infrastructure-as-code practices using tools like Terraform or CloudFormation.
- Analyze and interpret large datasets to extract insights and develop predictive models for system performance enhancement.
- Identify performance bottlenecks in systems and applications and utilize profiling tools to analyze resource usage (CPU, memory, I/O).
- Develop and implement data-driven solutions to optimize system parameters and improve throughput and latency.
- Design and implement observability systems for tracking key performance indicators (KPIs) using tools like Prometheus and Grafana.
- Establish and monitor Service Level Objectives (SLOs) and Service Level Indicators (SLIs).
- Create alerts for critical performance issues and incidents.
- Collaborate with development teams to integrate data science solutions into full stack application development.
- Communicate performance insights and recommendations to stakeholders through visualizations, reports, and presentations.
- Mentor junior SREs and data engineers on performance engineering and data-driven best practices.
Required skills and qualifications:
- Formal training or certification on software engineering concepts and 5 years applied experience
- Proficiency in programming languages such as REXX, Python, or Java.
- Strong understanding of statistical analysis, data engineering techniques focused on, monitoring, automation, and continuous improvement ensuring systems are efficient, scalable, and available.
- Experience with data manipulation and analysis using libraries such as Pandas, NumPy, TensorFlow, Scikit-learn, PySpark, or Polars.
- Familiarity with data visualization tools such as Matplotlib, Seaborn, Power BI, or Tableau.
- Knowledge of SQL and experience with database querying.
- Experience with mainframe and mid-range computing platforms.
- Proficiency with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
- Strong problem-solving, analytical, and communication skills.
Preferred qualifications:
- 5 years of experience in data science, SRE, or a related role, preferably in application development.
- Experience with full stack application development and optimizing system performance and reliability through software engineering principles.
- Knowledge of data engineering, ETL processes, and distributed systems architectures.
- Experience with DevOps principles and practices.
- Contribute to the automation of CI/CD pipelines.