Senior Site Reliability Engineer I

Renishaw-posted 3 months ago
Senior
5,001-10,000 employees
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LexisNexis Risk Solutions is a trusted partner in risk assessment. Within our insurance vertical, we provide customers with innovative solutions and decision tools that leverage public and industry-specific content, advanced technology, and analytics. Our products help drive informed, data-driven decisions across the insurance policy lifecycle, supporting operational efficiency and reducing risk.

  • Design, modify, develop, write, and implement data applications and REST APIs in cloud.
  • Develop microservices or middleware APIs under a micro-service styled architecture.
  • Fix issues in the existing systems by using the industry standard coding practices.
  • Interface with other technical personnel or team members to finalize requirements.
  • Write and review portions of detailed specifications for the development of complex system components.
  • Implement DevOps strategy in existing and new project.
  • Upgrade and enhance existing C++ applications to enterprise Java.
  • Work closely with other development team members to understand complex product requirements and translate them into software designs.
  • Successfully implement development processes, coding best practices, and code reviews.
  • Operate in various development environments (Agile, Waterfall, etc.) while collaborating with key stakeholders.
  • Resolve complex technical issues, as necessary.
  • Keep abreast of new technology developments.
  • Design and work with complex data models.
  • All other duties as assigned.
  • At least 7/8+ years of experience of software development programming with enterprise Java.
  • Proficiency in Java programming with Spring Framework.
  • At least 3 years of experience with Microservices asynchronous event driven programming or event messaging programming under a pub/sub model.
  • Strong secure coding and system vulnerability mitigation experience.
  • Strong experience in AI-assisted software development.
  • Strong knowledge of Docker containers, Docker CLI and strong practical knowledge of Kubernetes and Kubernetes CLI is desired.
  • Expertise in other development languages including but not limited to PowerShell, Python, and SQL is desired.
  • Strong knowledge of multiple data storage subsystems, especially relational databases including MySQL, Sybase, PostgreSQL, and/or Oracle.
  • Advanced knowledge of software development methodologies (e.g., Agile, Waterfall).
  • Strong proficiency with data manipulation language including optimization techniques.
  • Strong understanding of normalized/dimensional data modeling principles.
  • Strong research skills.
  • Strong proficiency with DevOps and Continuous Integration/Delivery tools and Linux bash scripting is desired: Gitlab, GitHub Actions, Ansible, Linux Bash scripting.
  • Strong experience working with one of the 2 major Cloud vendors (AWS, Azure) and/or a strong foundational understanding of Microsoft Azure Cloud IaaS and PaaS services offerings is desired.
  • Good to have Azure/AWS fundamental and/or developer certifications.
  • Experience with Azure Cloud services in particular running containerized workloads in Azure Kubernetes Services is a big plus.
  • Ability to interface competently with other technical personnel or team members to finalize requirements.
  • Ability to work well with internal and external technology resources.
  • Ability to partner and lead internal and external technology resources in solving complex business needs.
  • Knowledge of test-driven development and unit testing frameworks/methodologies.
  • Ability to write and review portions of detailed specifications for the development of complex system components.
  • Good oral and written communications skills.
  • 7/8+ years of Software Engineering experience.
  • B.Sc. (IT)/B.Sc. (CS)/BCA/MCA/BE (Computers/IT) or equivalent experience required.
  • Good to have Azure/AWS fundamental and/or developer certifications.
  • Experience with Azure Cloud services in particular running containerized workloads in Azure Kubernetes Services is a big plus.
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