Data Center Manager

A Data Center Manager is responsible for the management and maintenance of a data center, ensuring optimal performance, security, and disaster recovery capabilities.
Salary Insights
High-ROI Certifications
Potential Lateral Jobs
Publications/ Groups

Data Center Manager

Payscale
Market
National (USA)
Base Salary
$101,894 / year
Satisfaction
Additional Benefits
Yes
Industry
All
Education
Master's Degree

The average salary for Data Center Manager is $101,894 / year according to Payscale.com

There are no updated reports for Data Center Manager salaries. You can check potential lateral job opportunities in this information stack to find related salary information.

Data Center Manager role may have an alternate title depending on the company. To find more information, you can check Payscale.com.

Career Information

As a Data Center Manager, you will be responsible for overseeing the operations and maintenance of an organization's data center facilities. You will need strong knowledge of data center infrastructure and technologies, as well as excellent problem-solving and project management skills. Proficiency in data center management tools and best practices is also important, as you will be responsible for managing capacity, ensuring uptime, and implementing disaster recovery plans.

The average salary for Data Center Manager is $101,894 / year according to Payscale.com
AI Disclaimer
The following text about the Job role of Data Center Manager has been generated by an AI model developed by OpenAI. While efforts have been made to ensure the accuracy and coherence of the content, there is a possibility that the model may produce hallucinated or incorrect information. Therefore, we strongly recommend independently verifying any information provided in this text before making any decisions or taking any actions based on it.

A Data Center Manager is responsible for the day-to-day operations of a data center. They are responsible for ensuring the data center is running efficiently and securely, and that all systems are up and running. They must also ensure that the data center is compliant with all applicable laws and regulations.

The most important skills for a Data Center Manager include strong technical knowledge, excellent communication and organizational skills, and the ability to troubleshoot and resolve technical issues. They must also have a good understanding of data center operations, including power, cooling, and security.

The primary tasks of a Data Center Manager include managing the data center infrastructure, monitoring system performance, and ensuring the data center is secure. They must also ensure that all systems are up and running, and that all data is backed up and stored securely. They must also be able to troubleshoot and resolve any technical issues that arise.

Data Center Managers must also be able to manage and maintain the data center budget, and ensure that all costs are kept within the allocated budget. They must also be able to develop and implement policies and procedures to ensure the data center is running efficiently and securely.

Finally, Data Center Managers must be able to work with other departments and teams to ensure that the data center is running smoothly. They must also be able to work with vendors and suppliers to ensure that the data center is properly maintained and that all systems are up and running.

Potential Lateral Jobs
Explore the wide range of potential lateral job opportunities and career paths that are available in this role.

High-ROI Programs

Most roles require at least a bachelor's degree. To remain competitive, job seekers should consider specialization or skill-specific programs such as specialization, bootcamps or certifications.
Certification Programs
Consider pursuing specialized certifications or vendor-specific programs to enhance your qualifications and stand out in the job market.

Microsoft Certified: Azure Data Scientist Associate

DP-100

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Databricks Certified Data Engineer Associate

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Microsoft Certified: Azure Data Engineer Associate

DP-203

The Microsoft Certified: Azure Data Engineer Associate program is designed for professionals who have expertise in integrating, transforming, and consolidating data from various structured, unstructured, and streaming data systems.

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Google Certified Professional Data Engineer

The Google Certified Professional Data Engineer is a high-ROI program designed for experienced professionals to become highly equipped with specialty skills and functional knowledge in cloud data engineering.

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AWS Certified Data Analytics — Specialty

DAS-C01

The AWS Data Analytics Certification program validates a deep understanding of AWS data analytics services and their integration with each other to derive insights from data, making it suitable for individuals pursuing a role focused on data analytics.

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Microsoft Certified: Azure Enterprise Data Analyst Associate

DP-500

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AWS Certified Machine Learning — Specialty Certification

MLS-C01

The AWS Certified Machine Learning - Specialty certification covers a wide range of topics, including data engineering, exploratory data analysis, modeling, and machine learning implementation and operations on the AWS Cloud. 

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Google Certified Professional Machine Learning Engineer

The Google Machine Learning Certification is a high-ROI program designed for ML engineers who want to gain specialized machine learning skills using Google Cloud technologies.

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Specialty Courses improving
If you want to improve your skills and knowledge in a particular field, you should think about enrolling in a Nanodegree or specialization program. This can greatly improve your chances of finding a job and make you more competitive in the job market.

Cloud Engineer Bootcamp

Mentorship

This high-ROI Cloud Engineering Bootcamp covers Linux, networking, DevOps, SRE, Kubernetes, and more, enabling you to excel in the high-paying, consumption-driven tech industry.

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Advanced Cloud Engineer Bootcamp

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This advanced cloud engineering bootcamp is for aspiring cloud engineers to develop a specialty for developing and operating cloud-based applications and services.

Data Engineer Career Track

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This career track is designed for beginners to learn Python basics, build data architecture, streamline processing, and maintain large-scale systems. Participants will develop pipelines, automate tasks, and construct high-performance databases using Shell, SQL, and Scala.

Data Engineering for Data Scientists

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This Nanodegree program teaches you how to access data silos, extract information from various sources, and streamline it into functional formats for analysts and high-level decision-makers. You will have the opportunity to create an impressive, machine learning-driven web application with significant real-world, life-saving implications.

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Data Engineering with Microsoft Azure

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You will acquire the skills to design data models, create data pipelines, and navigate large datasets on the Azure platform. Additionally, you will learn to build data warehouses, data lakes, and lakehouse architecture.

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IBM Data Engineering Professional Certificate

Professional

Become a Data Engineer

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This Nanodegree program equips learners with a strong foundation in Big Data Engineering. You will learn thoroughly about data models, data warehouses, data lakes, and data pipelines while working with massive datasets.

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Resource Stacks

We are soon crowdsourcing these resource stacks to collate the best resources, such as publications, community groups, job boards, etc., that are practically suitable for every contextual stack.
Publications
Discover the wide array of publications that professionals in this role actively engage with, expanding their knowledge and staying informed about the latest industry trends and developments.
Communities updating
Discover the thriving communities where professionals in this role come together to exchange knowledge, foster collaboration, and stay at the forefront of industry trends.
Research updating
We are currently in the process of updating contextual resources and we will be adding the new ones to the list shortly.
AI Disclosure: We are testing AI technologies to ensure the accuracy and coherence of recommendations. However, it is important to note that there is a possibility that the model may create hallucinated or incorrect inferences. Therefore, we highly recommend independently verifying any information provided in these stacks before making any decisions or taking any actions based on it.
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