A Data Product Manager oversees the development and implementation of data-driven products, ensuring alignment with business goals and user needs.
Potential Lateral Jobs
Data Product Manager
$113,454 / year
The average salary for Data Product Manager is $113,454 / year according to Glassdoor.com
There are no updated reports for Data Product Manager salaries. You can check potential lateral job opportunities in this information stack to find related salary information.
Data Product Manager role may have an alternate title depending on the company. To find more information, you can check Glassdoor.com.
As a Data Product Manager, you will be responsible for overseeing the development and launch of data-driven products and services. You will need strong project management and communication skills, as well as a deep understanding of data analytics and business strategy. Strong problem-solving and analytical skills are essential, as you will be responsible for identifying market opportunities and driving product innovation.
The following text about the Job role of Data Product Manager has been generated by an AI model developed by Cohere. 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.
The data product manager is a crucial role in any organization that deals with large amounts of data. This role is responsible for the development and implementation of data products, which are products that use data to solve a problem or meet a need. The data product manager works with a team of engineers, designers, and other professionals to create and launch these products.
The most important skills for a data product manager include:
Strong analytical skills: The data product manager must be able to analyze large amounts of data and identify trends and patterns.
Strong communication skills: The data product manager must be able to communicate complex ideas to a variety of stakeholders, including engineers, designers, and business leaders.
Strong project management skills: The data product manager must be able to manage the development and implementation of data products, ensuring that they are delivered on time and within budget.
Some of the most important tasks for a data product manager include:
Defining the scope and objectives of the data product: The data product manager must work with the team to define the scope and objectives of the data product, ensuring that it meets the needs of the organization and its users.
Leading the development of the data product: The data product manager must lead the development of the data product, working with the team to design and build the product.
Testing and launching the data product: The data product manager must test the data product to ensure that it is working correctly and is ready for launch. Once the product is ready, the manager must launch it to the public.
Monitoring and evaluating the data product: The data product manager must monitor and evaluate the data product after it has been launched, looking for ways to improve it and ensure that it is meeting the needs of the organization and its users.
Overall, the data product manager is a crucial role in any organization that deals with large amounts of data. This role is responsible for the development and implementation of data products, working with a team of professionals to create and launch products that use data to solve a problem or meet a need.
Potential Lateral Jobs
Explore the wide range of potential lateral job opportunities and career paths that are available in this role.
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.
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
The Microsoft Certified: Azure Data Scientist Associate is a high-ROI program designed for professionals who have expertise in applying data science and machine learning techniques to implement and manage machine learning workloads on Azure.
The Databricks Data Engineer Certification program is highly sought after, designed to evaluate an individual's proficiency in utilizing the Databricks Lakehouse Platform for performing fundamental data engineering tasks.
Microsoft Certified: Azure Data Engineer Associate
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.
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.
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.
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.
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.
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.
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.
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.
Discover the thriving communities where professionals in this role come together to exchange knowledge, foster collaboration, and stay at the forefront of industry trends.
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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