Manager Data Engineering DevOps

JOB SUMMARY: Responsible for leading the DevOps team within the data engineering function, focusing on automating, optimizing, and streamlining data pipelines and infrastructure to support robust continuous integration and continuous delivery (CI/CD) practices. This role integrates DevOps best practices with DataOps and Lean principles to ensure that deployment pipelines and automation frameworks are designed to meet the core needs of enterprise data management while also being adaptable to support advanced analytics initiatives, including AI, ML, and Data Science.

DUTIES & RESPONSIBILITIES:

Develop and implement comprehensive DevOps strategies for data engineering that align with overall organizational objectives.

Promote best practices in CI/CD, automation, and infrastructure as code (IaC), ensuring alignment with DataOps and Lean principles and incorporate requirements from traditional data management functions and advanced analytics initiatives into the DevOps strategy.

Lead, mentor, and manage the Data Engineering DevOps team, fostering a culture of continuous improvement, rapid iteration, and proactive incident management.

Lead the design, development, and deployment of automated data pipeline solutions, while implementing infrastructure as code for cloud and on-prem environments, and ensuring robust version control, configuration management, and automated testing in CI/CD pipeline.

Establish and track performance metrics for DevOps processes and data systems to ensure reliability and optimal performance and develop monitoring, observability, and incident response mechanisms to quickly identify and resolve issues.

Utilize methods such as Statistical Process Control (SPC) to maintain operational visibility and preemptively address potential problems.

Collaborate closely with data engineering, IT operations, and cross-functional business teams to embed DevOps practices throughout the data lifecycle and maintain open communication with stakeholders to ensure efficient deployment and continuous delivery of data products that address both core enterprise needs and advanced analytics requirements.

Design scalable CI/CD pipelines to support advanced analytics, integrating automated testing, continuous monitoring, and metadata capture to ensure high-quality data flows for AI, ML, Data Science, and operational workflows.

Evaluate, select, and manage third-party tools and vendors that support the DevOps environment and oversee vendor relationships to ensure that automation, orchestration, and monitoring tools meet operational and advanced analytics integration needs.

Champion the integration of Lean practices and DataOps principles within the DevOps framework to drive continuous process improvements and stay current with industry trends and best practices to enhance the capabilities of the DevOps team.

Identify and implement innovative solutions that accelerate product delivery and improve overall operational performance.

Perform other job-related functions as assigned. QUALIFICATIONS

DEGREE TYPE: Bachelor's Degree

FIELD(S) OF STUDY: Computer Science, Information Technology, or a related field; or an equivalent combination of education and relevant experience.

EXPERIENCE:

Minimum of 7 years' experience in DevOps, infrastructure management, and automation within data engineering or related fields.

Demonstrated expertise in developing and managing CI/CD pipelines using tools such as Jenkins, GitLab CI/CD, or similar.

Proven experience in supporting traditional data management functions while incorporating requirements for advanced analytics.

Proficiency in scripting languages (e.g., Python, Bash), containerization (e.g., Docker, Kubernetes), and infrastructure as code tools (e.g., Terraform, CloudFormation).

Experience working with cloud services (AWS, Azure, or GCP) and managing both cloud and on-premises infrastructures. COMPETENCIES/SKILLS:

Strong leadership and team management skills with a demonstrated ability to build high-performing teams.

Excellent communication, collaboration, and interpersonal skills.

In-depth understanding of DevOps principles, CI/CD, automation, and cloud-native architectures.

Proficiency with version control systems (e.g., Git) and configuration management tools (e.g., Puppet, Chef, Ansible).

Ability to manage multiple projects simultaneously in a fast-paced environment.

Strong analytical and problem-solving skills, with effective decision-making under pressure.

Familiarity with Agile methodologies and continuous improvement practices.

Understanding of advanced analytics workflows and the ability to design deployment pipelines that support requirements for AI, ML, and Data Science.

A proactive mindset committed to driving innovation and operational excellence.

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EQUAL EMPLOYMENT OPPORTUNITY:

Norwegian Cruise Line Holdings Ltd. and its subsidiaries are equal opportunity employers, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, protected veteran status, disability status, or any other characteristics protected by law. EEO is the law EEO is the law GINA Supplement

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