Software Engineer III - Tableau SRE And Automation
Talentmate
India
19th August 2026
2608-2545-5173
Job Description
Join our team to drive platform reliability and enhance user experience with innovative automation and operational excellence. Grow your career by collaborating with engineering, infrastructure, and security experts.
As a Software Engineer III at JPMorgan Chase within the Chief Technology Office team, you will ensure reliable access to internally built Tableau reporting solutions for external users through Authentication Everywhere (AuthE). You will partner with cross-functional teams to troubleshoot complex issues, drive automation, and improve platform stability. Your work will directly impact end-user experience and operational efficiency.
Job responsibilities
Provide production support and reliability engineering for Tableau reporting experiences.
Perform and automate platform health checks to reduce manual effort.
Implement exception-based monitoring and proactive alerting, tuning detection to improve signal quality.
Triage and resolve incidents using structured troubleshooting across logs, authentication signals, and Tableau telemetry.
Create, maintain, and execute operational runbooks, support procedures, and knowledge articles.
Participate in ITIL processes, including incident, problem, change, and release management.
Act as a liaison across dependencies, coordinate escalations, and track issues to closure.
Support performance, stability, and resiliency objectives, including capacity monitoring and failover readiness.
Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Required qualifications, capabilities and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Strong troubleshooting skills across Windows and Linux environments, including root cause analysis.
Experience with observability and monitoring platforms and log analysis tooling (e.g., Dynatrace, Splunk, Grafana).
Automation and scripting experience (Python and/or PowerShell) to reduce operational work and improve detection and response.
Experience working with APIs and integrations relevant to platform operations, including REST APIs and JSON payloads.
Experience executing changes and releases using controlled procedures, including familiarity with runbooks and post-deployment validation.
Working knowledge of networking and security fundamentals relevant to production support, including TLS/certificates, DNS, firewall/proxy concepts, and basic IAM concepts.
Strong documentation, communication, and stakeholder management skills.
Hands-on administration or production support experience with Tableau Server and/or Tableau Cloud.
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
Preferred qualifications, capabilities and skills
Experience supporting external-user authentication integrations and troubleshooting across OAuth2/OIDC and SAML, including certificate rotation/renewal.
Experience building automation to reduce operational toil and improve monitoring, reliability, and response time.
Experience partnering with engineering teams in a build-and-run model and driving post-incident improvements.
Familiarity with operational data formats and configuration patterns (JSON, YAML), and with secrets management and rotation concepts.
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