Who is a Data Product Manager? 9 Reasons You Need One!

Updated December 14th, 2023
who is a data product manager

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Without a dedicated figure like the data product manager, data initiatives might lack a clear direction or purpose, leading to wasted resources and failed projects.

According to a study made on data scientists, it was found that only 20% of the models made by a data scientist team go out for real production. This has encouraged companies to look into the importance of a data product manager.

Data product managers are the glue-binding technologists and business visionaries, guiding creations that transform organizations from the inside out.

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In this article, we will understand:

  1. Who a data product manager is, and 9 Reasons why you need one.
  2. Technical skills to look for while hiring a data product manager
  3. Difference between data product manager , data managers and data analyst

Ready? Let’s dive in!

Table of contents

  1. Who is a data product manager?
  2. 9 Reasons why you need a data product manager
  3. What are the roles and responsibilities of a data product manager?
  4. 8 Technical skills required to become a data product manager
  5. Job description of a data product manager
  6. Salary of a data product manager
  7. Data manager, data product manager and data analyst: What is the difference?
  8. Summing up
  9. Related reads

Who is a data product manager?

In the ever-evolving data landscape, a data product manager (DPM) stands as a beacon. Merging technical proficiency with business acumen, they shape how organizations leverage data for success.

The following are the key characteristics of data product managers:

  1. Role and significance of a data product manager
  2. Key tasks and day-to-day activities
  3. Essential skill set for a DPM
  4. Collaboration and interaction dynamics

Let’s look at the key characteristics of a data product manager in detail.

1. Role and significance of a data product manager

A data product manager (DPM) navigates the complex landscape of data-driven product development. They ensure the alignment of data initiatives with business goals.

Serving as the nexus between technical and business teams, the DPM translates intricate data insights into actionable business strategies. Their role is pivotal in turning data into a competitive advantage, ensuring organizations remain agile and forward-thinking in a data-rich environment.

2. Key tasks and day-to-day activities

Daily, a DPM oversees the life cycle of data products, from ideation to deployment. This involves crafting product roadmaps, prioritizing features, and ensuring timely delivery.

They’re also in constant dialogue with stakeholders, integrating feedback for product refinements. Ensuring data quality, security, and regulatory compliance are among their top responsibilities. Their day encapsulates a blend of strategy, communication, and oversight.

3. Essential skill set for a data product manager

A DPM boasts a hybrid skill set. Analytical prowess enables them to interpret complex data structures and trends. Product development acumen ensures they can transform data insights into tangible products.

Effective communication skills are paramount, allowing them to bridge the technical-business divide. Additionally, a firm grasp on ethics ensures that data usage respects privacy and regulatory norms.

4. Collaboration and interaction dynamics

Collaboration is at the heart of a DPM’s role. They work hand-in-hand with data scientists and engineers to sculpt data products. Regular interactions with business units ensure that these products are tailored to strategic needs.

Sometimes, they may also interface with external clients, customizing products to external requirements. In essence, a DPM’s success is often rooted in their ability to foster productive collaborations across diverse teams.

Serving as a bridge between data and its pragmatic application, the data product manager is central to a data-informed business environment. Their role, often intricate, ensures that data not only informs but transforms business strategies.

9 Reasons why you need a data product manager

A data product manager (DPM) plays a crucial role in organizations that aim to create or enhance data-driven products, features, or services.

As data becomes a central pillar of modern business strategy and decision-making, the DPM’s role becomes even more vital.

Here’s why a data product manager is needed:

  1. A bridge between technical and non-technical teams
  2. Focus on user needs
  3. Product lifecycle management
  4. Prioritization
  5. Collaboration & coordination
  6. Risk management
  7. Maintaining product-market fit
  8. Define metrics and KPIs
  9. Ensure ethical use of data

Let us understand the reasons in detail.

1. A bridge between technical and non-technical teams

A data product manager understands both the technical intricacies of data and the broader business objectives. They can translate complex data concepts into understandable insights for non-technical stakeholders and vice versa.

2. Focus on user needs

Data products, whether they’re internal tools for analysts or customer-facing features powered by algorithms, need to be user-centric. A DPM ensures that data products are designed and iterated based on user feedback and requirements.

3. Product lifecycle management

From ideation to retirement, a DPM oversees the entire lifecycle of a data product. They ensure that the product remains relevant, valuable, and aligned with business objectives, making decisions about feature additions, iterations, or product sunsetting as needed.

4. Prioritization

Resources (time, personnel, computing power) are always limited. A data product manager helps prioritize which features, improvements, or data initiatives will deliver the most value to users and the organization, ensuring efficient allocation of resources.

5. Collaboration & coordination

Building a data product often involves multiple teams—data scientists, engineers, UX designers, business units, etc. The data product manager acts as the central coordination point, ensuring all teams are aligned and working toward a common goal.

6. Risk management

Data products come with their own set of risks, from data privacy concerns to algorithmic biases. A data product manager understands these risks and ensures that they are mitigated, whether through product design, user education, or other means.

7. Maintaining product-market fit

As market needs change and technology evolves, data products need to adapt. A data product manager continually gauges the product-market fit and steers the product direction accordingly.

8. Define metrics and KPIs

The success of a data product can be nebulous without clear metrics. Data product managers can define and monitor key performance indicators (KPIs) to measure the success and impact of data products.

9. Ensure ethical use of data

With growing concerns about data ethics, a DPM plays a vital role in ensuring that data products are built and operated ethically, respecting user privacy and avoiding unintended consequences.

In essence, while traditional product managers bring value in guiding product development, the specialization of a data product manager is crucial in a world where products are increasingly powered by algorithms, AI, and vast amounts of data.

Their unique blend of data understanding, technical knowledge, and product management skills ensures that data-driven initiatives are successful, ethical, and aligned with business needs.

What are the roles and responsibilities of a data product manager?

A data product manager plays a crucial role in organizations that deal with data-driven products or services.

Here are the key roles and responsibilities of a data product manager:

1. Defining vision and strategy

The data product manager is responsible for setting the vision and strategic direction for data-centric products. This involves understanding the market, identifying customer needs, and aligning the product’s vision with the company’s broader strategy.

2. Product roadmap development

They create and maintain a product roadmap, outlining the timeline and key milestones for the development of the data product. This includes prioritizing features, planning releases, and ensuring alignment with customer needs and business goals.

3. Data understanding and utilization

A critical aspect of their role is understanding the data that powers the product. They need to know what data is available, how it can be used, and what limitations it might have. This understanding is key to making informed decisions about product development.

4. Cross-functional collaboration

Data product manager work closely with different teams, including data scientists, engineers, designers, and marketing professionals, to develop and implement the product. They need to communicate effectively across these teams to ensure that everyone is aligned with the product vision and goals.

5. Customer and market research

They conduct research to understand the needs and behaviors of the target audience. This research helps in making data-driven decisions about product features and improvements.

6. Analyzing product performance

They continuously analyze the performance of the data product, using metrics and feedback to understand user engagement and satisfaction. This analysis helps in making iterative improvements to the product.

7. Problem-solving and decision-making

Data product manager are often faced with complex problems that require data-driven decision-making. They must be adept at analyzing data, identifying trends, and making strategic decisions based on this analysis.

8. Ensuring compliance and data governance

They are also responsible for ensuring that the product complies with relevant laws and regulations, particularly those related to data privacy and security. They must understand the legal implications of handling data and ensure that the product adheres to these standards.

9. Stakeholder management

Managing expectations and communicating with stakeholders, including customers, senior management, and team members, is a key responsibility.

They need to ensure that all stakeholders are kept informed and that their inputs are considered in the product development process.

10. Innovation and continuous improvement

Finally, data product managers must foster an environment of innovation, encouraging their teams to come up with new ideas and approaches to improve the product continually.

In summary, a data product manager is at the intersection of business, technology, and data science, ensuring that data-driven products meet customer needs, align with business objectives, and are developed using the best available data and technology.

8 Technical skills required to become a data product manager

For a data product manager (DPM), technical skills are fundamental. These skills equip a data product manager to effectively liaise between the data teams and business stakeholders, ensuring the development of robust, usable, and impactful data products.

Key skills include:

  1. Data analytics & interpretation
  2. Familiarity with data tools & platforms
  3. Basic programming & scripting
  4. Understanding of machine learning & AI
  5. Database management & SQL
  6. Knowledge of data governance & security principles
  7. Systems architecture understanding
  8. API design & integration knowledge

Let us understand each of them in detail.

1. Data analytics & interpretation

A data product manager (DPM) dives deep into data to discern patterns, trends, and anomalies. They employ statistical tools and methods to make data-driven decisions.

This skill is paramount for a DPM because it helps them translate raw data into actionable insights, ensuring the data products they oversee provide tangible value and drive business outcomes.

2. Familiarity with data tools & platforms

Data tools like Tableau or PowerBI allow DPMs to visualize and interpret data, while platforms like Hadoop or Spark handle big data processing.

A data product manager should be well-versed with these to effectively communicate with data teams, set realistic product expectations, and know the limitations or possibilities of the tools and platforms in use.

3. Basic programming & scripting

Though not expected to code extensively, foundational knowledge in languages like Python, R, or JavaScript equips a data product manager to assess the feasibility of features and communicate more effectively with the development teams. It’s about understanding the art of the possible in the realm of data products.

4. Understanding of machine learning & AI

With many data products now leveraging predictive analytics, a DPM should have a grasp of basic machine learning concepts. This includes understanding training datasets, model evaluation, and the implications of different algorithms.

It ensures that they can guide product development in ML contexts and set realistic expectations.

5. Database management & SQL

Databases are the backbone of data products. A data product manager should understand relational and non-relational databases, and how data is stored, indexed, and retrieved.

Familiarity with SQL allows them to draft or comprehend queries, ensuring seamless communication with data engineers and a deeper understanding of data structure intricacies.

6. Knowledge of data governance & security principles

Data security and governance are non-negotiable. A DPM should be adept at understanding data protection regulations, encryption methods, and best practices in data storage.

This ensures the products they manage are compliant, and secure, and upholds the trust of users and stakeholders.

7. Systems architecture understanding

Knowledge of system integrations, cloud platforms, and how different components of a product interact is vital.

A DPM should understand scalability issues, potential bottlenecks, and how data flows within system architectures to guide the development of robust and efficient data products.

8. API Design & integration knowledge

Data products often interface with other systems. A data product manager needs to understand API protocols, how they’re designed, and their integration points.

This ensures seamless data exchange between systems, enriching the functionality and utility of the data products they manage.

In essence, the technical skills of a data product manager span a spectrum, from hardcore data analytics to systems design. This diverse skill set ensures they’re well-equipped to oversee the development of holistic, efficient, and impactful data products.

Job description of a data product manager

In recent years the job of a data product manager has been in significant demand. This is mainly because of the fact that data has become the new oil. Companies, regardless of the market of their operations are looking to harness the power of data to reach out to their target customers better and fulfill their needs and demands.

Let’s look at the job description of a data product manager.

Job summary

We are seeking a highly motivated and experienced data product manager to lead the development and management of our data products portfolio.

As a data product manager, you will play a pivotal role in defining our data product strategy, collaborating with cross-functional teams, and ensuring the successful delivery of data-driven solutions that align with our business objectives. This role requires a deep understanding of data analytics, technology, and strong project management skills.

Key responsibilities

  1. Data product strategy: Define and communicate the vision, goals, and roadmap for our data product offerings in alignment with the company’s strategic objectives.
  2. Product development: Oversee the end-to-end development lifecycle of data products, from concept to launch, including defining product requirements, managing resources, and ensuring on-time delivery.
  3. Data governance: Establish and maintain data governance policies and procedures to ensure data quality, compliance, and security, while adhering to industry best practices and regulations.
  4. Market research: Conduct market analysis and stay updated on industry trends to identify opportunities and threats, and make data-driven decisions regarding product enhancements and new offerings.
  5. User-centric approach: Prioritize user needs and gather feedback to shape data product features and functionality, ensuring they provide real value to both internal and external stakeholders.
  6. Cross-functional collaboration: Work closely with data scientists, engineers, analysts, and other stakeholders to define data product features, resolve technical issues, and drive successful product development.
  7. Data monetization: Explore opportunities to generate revenue from data products, such as through data licensing, partnerships, or the creation of data-driven subscription services.
  8. Performance monitoring: Continuously monitor data product performance using metrics and KPIs, and use insights to make adjustments and improvements, maximizing the impact on the business.
  9. Communication skills: Effectively communicate complex technical concepts to non-technical stakeholders and vice versa, fostering collaboration and understanding across teams.
  10. Adaptability: Stay up-to-date with emerging data technologies and methodologies, remaining adaptable and open to learning in a rapidly evolving data landscape.


  • Bachelor’s degree in a related field (Master’s preferred).
  • Proven experience in data product management or a similar role.
  • Strong knowledge of data analytics, data management, and data governance.
  • Excellent project management and organizational skills.
  • Exceptional communication and interpersonal skills.
  • Ability to work collaboratively in a cross-functional team environment.
  • Proficiency in data analysis tools and technologies.
  • Familiarity with regulatory and compliance requirements related to data.

Join our team as a data product manager and be a driving force in shaping our data products, making a significant impact on our organization’s success through data-driven innovation.

Salary of a data product manager

The salary of a data product manager can vary significantly based on factors such as location, industry, level of experience, and the size and financial health of the company. However, we can provide a general salary range to give you an idea of what to expect.

In the United States, for instance, the salary of a data product manager typically falls within the range of $90,000 to $160,000 or more per year. Here’s a breakdown of how different factors can influence salary:

  1. Experience: Entry-level data product managers with a few years of experience might earn closer to the lower end of the range, while those with extensive experience and a proven track record in the field can command salaries at the higher end or beyond.
  2. Location: Salaries tend to be higher in major metropolitan areas with a high cost of living, such as San Francisco, New York City, and Seattle. In contrast, salaries may be lower in smaller cities and regions with a lower cost of living.
  3. Industry: Data product managers working in industries such as technology, finance, healthcare, and e-commerce often earn higher salaries due to the complexity and importance of data in these sectors.
  4. Company Size: Larger companies and tech giants may offer more competitive salaries, as well as additional perks and bonuses, compared to smaller startups or non-profit organizations.
  5. Education: Having an advanced degree, such as a Master’s in Data Science or Business Administration (MBA), can sometimes result in a higher starting salary.
  6. Skills and Expertise: Specialized skills in areas like machine learning, artificial intelligence, data engineering, or data security can also lead to higher compensation.

It’s essential to research salary ranges specific to your location and industry when considering a data product manager position. Additionally, negotiating skills and the ability to showcase your qualifications and accomplishments can impact your final salary offer. As the field of data continues to evolve and grow in importance, data product managers can anticipate competitive compensation packages.

Data manager, data product manager and data analyst: What is the difference?

Data manager, data product manager, and data analyst play distinct roles within the realm of data management and analysis.

Here’s a breakdown of the primary differences:

1. Data manager

  • Role & responsibilities:

    • Manage and oversee the organization’s data infrastructure, ensuring data integrity, security, and availability.
    • Establish and maintain data governance, data quality standards, and data lifecycle management.
    • Collaborate with IT and data engineering teams to design and implement data storage and access solutions.
    • Define and enforce data backup, archival, and disaster recovery procedures.
  • Skills: Database management, data governance, data quality, data lifecycle management, knowledge of relevant data storage and processing technologies.

Primarily concerned with the underlying infrastructure and processes that ensure data is stored, maintained, and accessible in a safe and reliable manner.

2. Data product manager

  • Role & responsibilities:

    • Envision and drive the development of data-driven products, services, or features.
    • Translate business requirements and stakeholder needs into product requirements for data products.
    • Collaborate with data scientists, engineers, and analysts to build and launch data products.
    • Monitor the performance of data products and iterate based on feedback and evolving requirements.
  • Skills: Product management, understanding of data analytics and machine learning (to a degree), stakeholder communication, project management.

Primarily concerned with delivering valuable data-centric products or features to end-users or other stakeholders, bridging the gap between technical and non-technical teams.

3. Data analyst

  • Role & responsibilities:

    • Analyze data to derive insights and inform business decisions.
    • Use statistical tools and methods to identify trends, anomalies, and patterns in data.
    • Generate reports, dashboards, and visualizations to communicate findings to stakeholders.
    • Work closely with business units to understand their data needs and provide analytical support.
  • Skills: Data wrangling, statistical analysis, tools like SQL, Excel, Python, R, and BI platforms (e.g., Tableau, Power BI).

Primarily concerned with extracting insights from data to drive informed business decisions.

In essence

  • A Data manager ensures that data is stored, accessible, and governed properly.
  • A Data product manager drives the creation and improvement of data-driven products or services.
  • A Data analyst dives into data to extract actionable insights for the business.

These roles can exist within the same organization, and they often collaborate to ensure the efficient use and flow of data to drive business value.

Summing up

As data becomes entrenched across every facet of business, so too does the need for multidisciplinary figures that can extrapolate insights and manifest competitive advantage. Enter the data product manager - equipped with technical acumen, product intuition and strategic vision to transform raw analytics into business success.

Data product managers serve a profound role as the connective tissue between data science and pragmatic decision-making, guiding the development of intelligent products tailored to business objectives.

Organizations that invest in cultivating top-notch data product managers will be best positioned to unlock the richness of data and pioneer the future with confidence.

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