76 to 100 of 3,529 Agile-Software-Development Jobs

Windows server operating systems. Expertise in scripting languages such as Python, PowerShell & Shell. Strong incident fault finding skills and experience. Familiarity with ITSM, Agile methodologies and tools eg Azure DevOps, ServiceNow Good communication and problem-solving skills. #LI-EU What’s in it for you At Accenture ...

senior management and other key stakeholders. Contributing to the application of best practices in project management, software development lifecycle (SDLC), and Agile methodologies. Helping communication and collaboration between internal teams and external vendors or partners, in a fast paced, multi-vendor environment Providing technical leadership ...

from concept to deployment—while championing best practice, mentoring developers, and contributing to our strong engineering culture. Working within an Agile environment, you’ll collaborate with Product, Architecture, and cross-functional teams to deliver new features, improve code quality, drive innovation, and continually enhance the developer experience. What …/JavaScript, SQL/Postgres, AWS). Lead on technical delivery of new features and greenfield development across our platforms. Engage in Agile planning, estimation, and design discussions to shape solutions and deliver to agreed timeframes. Contribute to code reviews and promote engineering excellence, performance, security ...

/Jira/Confluence/M365 Preferred Skills Experience with cloud platforms (Azure/AWS) and containerization (Docker/Kubernetes). Familiarity with Agile/Scrum methodologies. Strong knowledge of performance optimization and security best practices. Experience with CI/CD pipelines and Infrastructure as Code. Excellent leadership ...

improvement Bonus Points For Experience in microservices architecture and containerization (Docker, Kubernetes) Exposure to CI/CD pipelines and DevOps practices Background in agile methodologies and delivery management Contributions to open-source Java libraries or frameworks Why Join Them? Work with brilliant, passionate engineers Real ownership & influence over ...

Cloud, containerisation (Docker, Kubernetes). Strong programming experience in one or more of JavaScript, Java, .Net, or Python Proven experience working within agile environments using Scrum, Lean, or Kanban methodologies Knowledge of CI/CD pipelines and automated testing frameworks Understanding of common software design patterns ...

documentation and problem-solving skills A Business, Finance, Science or Mathematics degree or qualification and relevant business experience in a similar role PMP, Agile certification or equivalent preferred (not required) Good Excel-based spreadsheet/quantitative and data management skills Familiarity with SDLC - BA and project management methodology ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...