高级 DevSecOps 工程师
Sr. DevSecOps Engineer
EBSCO Information Services (EBSCO) 提供一个完全优化的研究体验，与强大的发现平台无缝集成，以满足最终用户的信息需求并最大化研究体验。总部位于马萨诸塞州伊普斯维奇，EBSCO 在全球拥有超过 2700 名员工，大多数采用混合或远程办公模式。作为一家具备人工智能功能的服务领导者，我们致力于创新、前瞻性策略以及卓越团队的奉献精神。在 EBSCO，我们致力于激发、赋能和支持研究。我们的使命是通过提供可靠且相关的信息来改变人们的生活——在人们需要的时候、地点和方式。我们正在寻找充满活力、富有创造力的个体，他们的多元视角将帮助我们实现这一全球性、包容性的使命。加入我们，一起创造影响。
你的机会
作为高级 DevSecOps 工程师，你将在基于 AWS 的数据湖屋生态系统中，负责设计、构建和维护生产级别的数据和平台流水线及基础设施。与数据工程师和其他工程团队合作，你将实现工作负载的运维，并确保平台生命周期的可靠性、安全性和可扩展性，从数据采集到部署和监控。
你将帮助塑造我们的 DevSecOps 框架，为加速交付做出贡献，并确保符合已建立的平台非功能性需求（NFR）。这是一个高度协作、动手能力强的工程岗位，要求对 AWS 服务、自动化和工作流编排有深入理解，并且对软件开发最佳实践有坚定的承诺。
该职位为远程办公，工作于分布式敏捷环境。
你会做什么
· 设计、构建和维护支持跨 AWS 环境的工作负载打包、验证和部署的自动化流水线。
- 使用 CI/CD 最佳实践实现打包、测试、部署和监控的自动化。
- 与数据工程师和其他工程团队合作，实现在数据湖屋生态系统中的工作负载运维。
- 开发和维护数据采集、存储和下游服务仓库之间的集成。
- 使用基础设施即代码（Terraform、AWS CDK、CloudFormation）构建可重用、可组合的结构和模块，这些结构和模块通过自动化测试进行版本控制和验证，而不是由临时脚本拼接而成。
- 实现一个
查看英文原文
EBSCO Information Services (EBSCO) delivers a fully optimized research experience, seamlessly integrated with a powerful discovery platform to support the information needs and maximize the research experience of our end-users. Headquartered in Ipswich, MA, EBSCO employs more than 2,700 people worldwide, with most embracing hybrid or remote work models. As an AI-enabled service leader, we thrive on innovation, forward-thinking strategies, and the dedication of our exceptional team. At EBSCO, we’re driven to inspire, empower and support research. Our mission is to transform lives by providing reliable and relevant information — when, where and how people need it. We’re seeking dynamic, creative individuals whose diverse perspectives will help us achieve this global, inclusive mission. Join us to help make an impact.Your Opportunity
As a Senior DevSecOps Engineer, you will play a key role in designing, building, and maintaining production-grade data and platform pipelines and infrastructure within our AWS-based data lakehouse ecosystem. Working alongside data engineers and other engineering teams, you will operationalize workloads and ensure the reliability, security, and scalability of the platform lifecycle, from data ingestion through deployment and monitoring.
You will help shape our DevSecOps framework, contribute to automation that accelerates delivery, and ensure alignment with established platform Non-Functional Requirements (NFRs). This is a highly collaborative, hands-on engineering role requiring a deep understanding of AWS services, automation, and workflow orchestration, along with a strong commitment to software development best practices.
This position is remote and operates within a distributed agile environment.
What You'll Do
· Design, build, and maintain automation pipelines supporting workload packaging, validation, and deployment across AWS environments.
- Implement automation for packaging, testing, deployment, and monitoring using CI/CD best practices.
- Collaborate with data engineers and other engineering teams to operationalize workloads within the data lakehouse ecosystem.
- Develop and maintain integrations between data ingestion, storage, and downstream service repositories.
- Apply infrastructure-as-code (Terraform, AWS CDK, CloudFormation) to build reusable, composable constructs and modules that are version-controlled and validated through automated tests, rather than one-off scripts glued together.
- Implement and manage versioning, reproducibility, and lineage tracking for pipeline artifacts and configurations.
- Define and automate monitoring, alerting, and remediation strategies for deployed services.
- Ensure all infrastructure and pipelines meet enterprise security, compliance, and governance standards.
- Participate in code reviews, knowledge sharing, and continuous improvement of DevSecOps practices.
- Mentor junior engineers and contribute to documentation, standards, and best practices for software delivery across teams.
Your Team:
This role is part of the Data & AI organization, focusing on the operationalization of pipelines and platform infrastructure within AWS. Areas of specialty include:
· Pipeline automation and orchestration
- Versioning, governance, and observability
- Testable, modular infrastructure-as-code practices
- Secure, compliant, and scalable platform infrastructure
- Continuous improvement of lifecycle automation
About You
· 6+ years of professional experience in software or data engineering.
- 3+ years of direct experience implementing and maintaining production pipelines and infrastructure.
- Strong proficiency in Python and solid software engineering fundamentals (testing, code review, version control).
- Hands-on experience with AWS services (Step Functions, Lambda, ECR, S3, Glue, IAM, CloudWatch).
- Solid understanding of CI/CD, containerization (Docker)
- Experience with building CI/CD pipelines (Jenkins, Github Actions, etc.).
- Experience building reusable, composable infrastructure-as-code (Terraform, AWS CDK, or CloudFormation) as true, testable constructs, not just automation scripts.
- Strong understanding of data pipelines, ETL/ELT concepts, and data modeling in a lakehouse environment.
- Proven ability to apply software engineering best practices, including version control, automated testing, and code review, to infrastructure and data workflows.
- Strong communication and collaboration skills across multidisciplinary teams.
What sets you apart:
· Experience with AWS CDK.
- Experience with Github Actions.
- Experience with data catalogs and metadata management.
- Familiarity with data governance and compliance frameworks.
- Experience with observability and monitoring tooling (CloudWatch, or custom solutions).
- Understanding of data lakehouse technologies such as Apache Iceberg or Delta Lake.
- Contributions to open-source DevOps tooling.
- Experience in Agile development environments and cross-functional collaboration.
Pay Range
USD $124,750.00 - USD $178,215.00 /Yr.Originally posted on Himalayas