AWS Lead Software Engineer - Big Data ETL

Salary: $61,000 - 101,000 per year Requirements:

• We require formal training or certification in software engineering concepts, along with 5+ years of applied experience.
• We look for a strong record of designing, coding, testing, and delivering production-ready software in at least one technology stack.
• We need advanced development experience in Java or Python, plus strong debugging and troubleshooting ability for complex production issues.
• We value hands-on experience with AWS or other cloud platforms and container orchestration technologies such as Docker, Kubernetes, or ECS.
• We require experience building scalable data processing and Big Data/ETL pipelines, including AWS-based or Hortonworks solutions.
• We expect working knowledge of core infrastructure, including routers, load balancers, compute, storage, networks, and cloud products, with the ability to troubleshoot common networking issues.
• We need deep proficiency in reliability, scalability, performance, security, enterprise architecture, and toil reduction, with the ability to apply SRE practices to applications and platforms.
• We look for proficiency in white-box and black-box monitoring, SLO alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, or Splunk.
• We want candidates who can learn and assess new technologies, teach languages to others, and collaborate across levels and stakeholder groups.
• We require strong foundations in software applications and processes, with emerging depth in a discipline and the ability to solve complex data structures and algorithms problems.
• We seek demonstrated experience leading effective use of approved AI-assisted software development tools, with the ability to set expectations for validating AI outputs for correctness, performance, and security.
• We need a strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and alignment with resiliency and security expectations.
• We prefer a current AWS credential such as Cloud Practitioner, Solutions Architect, SysOps Administrator, or Developer.
• We also prefer a recognized automation or DevOps credential such as Kubernetes/containers, CI/CD, Infrastructure as Code, or site reliability.

• We design, code, test, and deliver automation, including LLMs and agents, to reduce manual operational work and streamline remediation efforts.
• We govern application risk, controls, and compliance by owning adherence to firm standards, partnering with Technology Risk & Controls, managing Technology Lifecycle Management, and driving closure of issues and findings.
• We own security and data accountability for the application, including authentication, authorization, vulnerability and certificate hygiene, and compliant data registration, classification, storage, retention, and disposal.
• We coordinate across product and engineering teams to prioritize and drive execution with urgency for AO workstreams.
• We run resilient, well-operated production services end to end, including monitoring, logging, anomaly detection, secure network configuration, least privilege, incident and problem management, change management, and recovery readiness.
• We demonstrate and champion site reliability culture and practices while influencing technical direction across the team.
• We lead initiatives that improve reliability and stability using data-driven analytics to raise service levels.
• We collaborate to define service level indicators and work with stakeholders to establish service level objectives and error budgets.
• We document and share knowledge through internal forums and communities of practice.
• We drive adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, while enforcing validation standards and encouraging reuse of effective patterns.
• We apply knowledge of SDLC toolchains, including enterprise-authorized AI-assisted development and automation capabilities, to increase the value delivered by automation.

• AI
• AWS
• Architect
• Big Data
• CI/CD
• Cloud
• Datadog
• DevOps
• Docker
• Dynatrace
• ETL
• Grafana
• Support
• Java
• Kubernetes
• Marketing
• Network
• Prometheus
• Python
• Security
• Splunk
• IAM

More:

Hackajob is collaborating with us at J.P. Morgan to connect exceptional professionals with this opportunity. We offer a role within JPMorgan Chase, one of the oldest financial institutions, where our teams deliver innovative financial solutions to millions of consumers, small businesses, and prominent corporate, institutional, and government clients. The position sits within the Corporate Sectors Model Delivery and Platform Engineering team, part of our Corporate Functions organization, where we work across finance, risk, human resources, and marketing to support our business, clients, customers, and employees. We offer a competitive total rewards package, with base salary based on role, experience, skills, and location, and eligible roles may include commission or discretionary incentive compensation. Our benefits and programs may include comprehensive health care, on-site wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, and financial coaching. We are committed to diversity and inclusion, equal opportunity, and reasonable accommodations where needed.

last updated 36 week of 2026