Schlumberger

Back End Software Engineer

Schlumberger$90K — $130K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Master's degree in Embedded System Technologies, Computer Science, or related STEM field.
  • 3 years of experience in designing and deploying applications with Kubernetes.
  • Proficiency in Google Cloud Platform services like GKE and Compute Engine.
  • Strong skills in Java programming for high-performance service development.
  • Experience with Python and bash for automation tasks.
  • Familiarity with Azure services such as Storage accounts and AKS.
  • Knowledge of statistical analysis and application performance optimization.

Responsibilities

  • Develop server-side logic and maintain the central database.
  • Ensure high performance and responsiveness of server-side applications.
  • Collaborate with front-end developers to integrate user-facing elements.
  • Build prototypes and products that meet project quality standards.
  • Provide technical leadership and create documentation for the team.
  • Support reuse through well-documented common components.
  • Maintain knowledge of emerging technologies and development best practices.

Benefits

  • Support for professional development and knowledge sharing.
  • Flexible working environment that encourages innovation.
  • Collaboration with a diverse team of skilled professionals.
Full Job Description
Full-time or part-time: Full-time

Job title: Back End Software Engineer

Job Location: 1430 Enclave Pkwy, Houston, TX 77077

Job Description:

Development of all server-side logic, definition and maintenance of the central database, and ensuring high performance and responsiveness to requests from the front-end. Integrate userfacing elements developed by a front-end developer with server-side applications. Collaborate with the front-end developers, customers, users, and product managers to establish objectives and design more functional, cohesive codes to enhance the user experience. Build prototypes, products and systems that meet the project quality standards and requirements. Provide technical leadership and documentation to developers and stakeholders. Contribute to and support re-use through common components that are well documented and tested. Apply the concepts of cloud computing and design patterns gained through experience to build, design and implement scalable cloud-based services and applications for PaaS, IaaS or SaaS. Utilize the concepts of Linux internals learnt from coursework Embedded Linux and Embedded Networking to create and run server node clusters to run backend applications. Use computer science concepts like data structures, algorithms and object-oriented design to create robust production quality applications and develop prototypes quickly. Author documentation, reports, papers, articles, patents and presentations for purposes of training and knowledge sharing purposes. Following the general development practices and techniques such as unit testing, integration testing, security testing and code quality measurement. Maintain familiarity with emerging technologies. Work with end users, product analysts, and developers to understand features and technical implementations.

Minimum Education & Experience Requirements:

Master's degree in Embedded System Technologies, or Embedded Systems Engineering, or Computer Science, or Electronics and Communication Engineering, or a related STEM field, or a foreign educational equivalent plus 3 years of post-baccalaureate experience in job offered or any engineering/developer related job titles. Applicants must have 3 years of experience in the following: (1) designing, developing, and deploying scalable applications using Kubernetes stack; (2) Google Cloud Platform services: GKE, GCR, Compute Engine, Stackdriver, and Cloud Storage; (3) Java programming to develop performant services; (4) Automation through python and bash scripting; (5) Developing batch applications and managing infrastructure for batch applications; (6) Profiling and optimizing application performance and tuning platform resources; (7) statistical analysis of data collected and reporting; and (8) Azure services including Storage accounts, ACR, and AKS.

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