Lead technical reliability efforts for data products: set SLOs/SLIs, run resiliency design reviews, drive CI/CD and IaC standards, mentor engineers, lead incident response, and optimize capacity and cost across cloud and on-prem systems.
Build systems that stay available when it matters most. In this role, you’ll shape how reliability is engineered across critical data products and platforms at JPMorganChase. You’ll partner with engineers and stakeholders to set measurable service goals, reduce toil through automation, and raise operational standards. You’ll have room to lead, mentor, and influence technical direction while tackling complex, high-impact challenges. If you’re passionate about scalable, secure, and resilient systems, you’ll thrive here.
As a Lead Site Reliability Engineer in Corporate Technology: Data Strategy & Architecture, you will lead resiliency design reviews and champion site reliability practices across medium to large-sized products. You will break down complex problems into actionable work, guide delivery through strong engineering standards, and help teams improve reliability using data-driven insights. You will serve as a technical leader during major incidents and influence solutions across multiple technical domains. You will mentor engineers and advise on technical and business issues to improve outcomes for customers and stakeholders. This is a technical leadership (IC) position, rather than a team leadership position.
Job Responsibilities
- Champion site reliability culture and practices, exerting technical influence across the team
- Lead initiatives to improve reliability and stability using data-driven analytics to improve service levels
- Partner with engineers and stakeholders to define service level indicators, service level objectives, and error budgets
- Identify and resolve technical bottlenecks across one or more technical domains
- Act as a primary point of contact during major incidents, driving rapid diagnosis and resolution to reduce impact
- Document and share knowledge through internal forums and communities of practice
- Define and drive CI/CD strategy and pipeline standards, including artifact management, environment promotion, and release gating
- Design and implement infrastructure-as-code practices to enable self-service provisioning and reduce toil
- Lead resiliency design reviews for new and existing data products, identifying single points of failure, capacity risks, and operational gaps before production
- Embed shift-left security practices into delivery pipelines, including automated scanning, secrets management, and policy-as-code
- Lead capacity planning and cost optimization across cloud and on-premise compute for data workloads
Required Qualifications, Capabilities, and Skills
- Advanced knowledge of site reliability engineering practices, including reliability, scalability, performance, security, enterprise architecture, and toil reduction
- Proficiency in at least one programming language (e.g., Python, Java Spring Boot, .NET)
- Experience designing, implementing, and operating observability practices (e.g., white/black box monitoring, SLO alerting, telemetry collection) using tools such as Grafana, Dynatrace, Prometheus, Datadog, or Splunk
- Hands-on experience designing and operating CI/CD pipelines and release automation (e.g., Jenkins, GitLab CI, GitHub Actions, Argo CD)
- Proficiency in infrastructure-as-code and configuration management tooling (e.g., Terraform, Ansible, Helm)
- Experience with containers and orchestration (e.g., Docker, Kubernetes, ECS)
- Ability to troubleshoot common networking technologies and issues
- Ability to identify and solve problems involving complex data structures and algorithms
- Ability to break down complex problems into clear, deliverable work for engineering teams
- Ability to collaborate across stakeholder groups and influence technical decisions
- Drive to self-educate and evaluate new technology
Preferred Qualifications, Capabilities, and Skills
- Experience in a data platform, data mesh, or data product engineering environment (e.g., Spark, Kafka, dbt, Airflow)
- Familiarity with cloud-native data services on AWS, Azure, or GCP
- Experience with GitOps workflows and progressive delivery patterns
- Knowledge of chaos engineering practices and tooling
- Experience mentoring engineers and driving engineering standards across teams
- Relevant certifications (e.g., CKA, AWS/GCP/Azure Solutions Architect, HashiCorp Terraform Associate)
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
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