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Senior Data Product Manager

Are you passionate about bridging the gap between technical teams and business stakeholders to unlock the true potential of data? The Senior Data Product Manager plays a pivotal role in ensuring seamless collaboration, effective communication, and measurable impact across our data ecosystem.

In this role, you will oversee the flow, governance, and strategic alignment of data across the organization. You will focus on improving cross-functional coordination, streamlining request intake processes, and ensuring transparency through clear documentation and structured task management. By optimizing the integration, storage, and aggregation of data across platforms such as BigQuery, dbt, Mixpanel, Segment, GTM, Klaviyo, OneSignal, and Firebase, you’ll help unlock the true value of our data initiatives.

This is an exciting opportunity for a results-oriented individual to bring clarity, structure, and strategic oversight to a growing data environment, enabling data-driven decision-making at scale.

Key Responsibilities

Data Ecosystem Management

  • Data Flow Oversight: Manage and oversee the integration, transformation, and aggregation of data across tools, ensuring consistency and reliability.
  • Tool Integration Management: Work closely with data engineers and tool owners to optimize the configuration and integration of platforms, improving data accessibility and performance.
  • Data Governance: Establish and enforce best practices for data transfer, storage, and aggregation, ensuring compliance with privacy regulations and organizational standards.

Cross-Functional Coordination

  • Facilitate collaboration between the data team, marketing, product, engineering, and operations to ensure alignment and smooth communication on shared data initiatives.
  • Establish processes to track ownership, deliverables, and responsibilities across teams.

CI/CD Communication for Data Releases

  • Develop and implement a clear communication framework to notify stakeholders about continuous integration and deployment (CI/CD) activities, including new releases, upgrades, and bug fixes.
  • Ensure stakeholders and end-users understand the business implications of ML output variations due to retraining or changes in the underlying data.

Request Intake and Prioritization

  • Create and manage a streamlined process for intake and clarification of data-related requests, ensuring requirements are well-defined and actionable.
  • Collaborate with stakeholders to prioritize requests based on business value, feasibility, and impact.

Impact Evaluation and Stakeholder Satisfaction

  • Design and implement metrics to measure the success, impact, and adoption of data initiatives, including ML models and dashboards.
  • Regularly gather feedback from stakeholders to assess satisfaction and identify areas for improvement.

Workflow and Task Management

  • JIRA Management: Oversee the structure and content of JIRA tickets and Epics, ensuring they are detailed, organized, and actionable for both small tasks and large projects.
  • Workflow Optimization: Maintain visibility into the progress of projects, ensuring timely delivery and clear updates to stakeholders.

Documentation Ownership

  • Develop and maintain comprehensive and up-to-date documentation for data processes, pipelines, CI/CD workflows, and governance policies.
  • Create resources to enable self-service and improve transparency for stakeholders company-wide.

Strategic Collaboration

  • Partner with leadership to ensure data team priorities align with broader organizational goals.
  • Advocate for data-driven decision-making by connecting technical capabilities with business needs.

Experience

  • Proven track record as a Data Product Manager or similar role, with experience managing complex data ecosystems and workflows.
  • Understanding of Martech and AdTech related data challenges

Technical Expertise (optional, but good to have)

  • Strong understanding of data pipeline architecture, integration processes, and analytics platforms.
  • Familiarity with SQL, ETL/ELT processes, and data warehousing best practices.
  • Hands-on experience with tools like BigQuery, dbt, Mixpanel, Segment, GTM, Klaviyo, OneSignal, and Firebase is highly desirable.

Problem-Solving Skills

  • Ability to analyze and resolve technical and workflow issues related to data flow and governance.

Leadership

  • Experience driving cross-functional collaboration and ensuring accountability for deliverables across technical and non-technical teams.

Communication

  • Exceptional ability to translate technical requirements into business terms and vice versa.

Project Management

  • Proficiency with project management tools and frameworks (e.g., JIRA, Epics, User Stories) to track deliverables and their impact.

Key Attributes

  • Strategic thinker with a proactive, solution-oriented mindset.
  • High attention to detail, especially regarding data quality and governance.
  • Comfortable navigating and managing priorities in a fast-paced environment.
  • Excellent organizational and leadership skills to align teams and drive outcomes.

This role is ideal for a seasoned data professional passionate about enabling seamless data-driven operations and optimizing the integration of tools and systems across a growing organization.

What You Should Know About Senior Data Product Manager, Reverse Tech

Are you ready to step into an exciting role as a Senior Data Product Manager with us? If you have a knack for connecting the dots between technical teams and business stakeholders, this could be your dream job! In this pivotal position, you’ll be focusing on optimizing our data ecosystem, managing data flow, and establishing governance practices that ensure our data initiatives deliver measurable outcomes. You’ll collaborate across teams, making sure that the data team, marketing, product, engineering, and operations are all harmoniously aligned on data-related projects. From streamlining request intake processes to overseeing tool integrations and maintaining clear documentation, your days will be filled with impactful tasks. You’ll get to dive into platforms like BigQuery, dbt, and Mixpanel, maximizing the value they bring to our organization. Not only will you evaluate the success and adoption of our data initiatives, but you’ll also be the person who communicates vital information regarding CI/CD activities to stakeholders. Your strategic oversight will support a culture of data-driven decision-making across the board. If you’re driven, organized, and have a passion for facilitating seamless operations within a growing data environment, we’d love for you to join our dynamic team and help us unlock the true potential of our data!

Frequently Asked Questions (FAQs) for Senior Data Product Manager Role at Reverse Tech
What are the main responsibilities of a Senior Data Product Manager at our company?

As a Senior Data Product Manager at our company, your primary responsibilities include overseeing data flow and governance, managing tool integrations, and facilitating cross-functional collaboration. You'll ensure that data-related requests are clearly defined and actionable, develop metrics to measure the success of data initiatives, and maintain thorough documentation. This role emphasizes coordination between technical and non-technical teams to drive effective data usage across the organization.

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What qualifications and experience are required for the Senior Data Product Manager position?

Candidates for the Senior Data Product Manager position should have a proven track record in managing complex data ecosystems and workflows. Typically, this involves having prior experience in a similar role, coupled with a strong understanding of MarTech and AdTech data challenges. Familiarity with tools like BigQuery, dbt, and Mixpanel—as well as knowledge of SQL, ETL/ELT processes—is highly desirable.

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How does the Senior Data Product Manager facilitate cross-functional collaboration?

The Senior Data Product Manager plays a key role in facilitating cross-functional collaboration by establishing processes to ensure clear ownership and accountability. By coordinating communication among the data team, marketing, product, engineering, and operations, you’ll help synchronize efforts on shared data initiatives and ensure everyone is informed about progress and outcomes.

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What tools and platforms does the Senior Data Product Manager work with?

In this role, you'll work with an array of platforms including BigQuery, dbt, Mixpanel, Segment, GTM, Klaviyo, OneSignal, and Firebase. These tools are crucial for managing data integration, transformation, and aggregation, enabling you to optimize their configuration for enhanced performance and accessibility.

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What soft skills are essential for a Senior Data Product Manager?

A successful Senior Data Product Manager should possess strong communication and leadership skills to effectively translate technical requirements into business terms. Problem-solving abilities, attention to detail, and a proactive, solution-oriented mindset are also crucial for navigating both technical challenges and team dynamics in a fast-paced environment.

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Common Interview Questions for Senior Data Product Manager
Can you explain your experience with data ecosystem management?

In your response, focus on specific instances where you successfully managed complex data flows, emphasizing tools and methods you used to ensure reliability and accessibility of data. Discuss your understanding of best practices in data governance and how you have fostered collaboration between teams.

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How do you prioritize data-related requests from various stakeholders?

When addressing this, highlight your approach to assessment based on business value, feasibility, and impact. Provide examples of frameworks or criteria you use to evaluate requests and ensure alignment with broader company goals.

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Describe a time when you improved a data integration process.

Share a concrete example that illustrates your problem-solving skills. Discuss the situation, the actions you took to improve the integration process, the impact on data accessibility, and the feedback from stakeholders afterward.

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How do you ensure effective communication around CI/CD release cycles?

Talk about the strategies you've implemented to inform stakeholders about CI/CD activities, such as establishing a clear communication framework. Mention how you conveyed the implications of data changes and the importance of staying informed for business transformations.

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What metrics do you find most effective for evaluating data initiatives?

You should focus on both qualitative and quantitative metrics. Discuss different types of metrics you have successfully tracked—such as adoption rates, impact on decision-making, or stakeholder satisfaction—and explain how these metrics guided future data strategies.

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Can you describe your experience with tools like JIRA for task management?

Discuss your familiarity with JIRA and how you've utilized it to manage tasks, workflows, and project epics. Provide examples of how structured ticketing and clear documentation have led to successful project completions.

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How do you foster a culture of data-driven decision-making in an organization?

Share your philosophy on promoting data-driven practices. Include strategies like advocating for the importance of data insights in meetings, providing relevant training to teams, or sharing success stories to encourage the use of data in decision-making processes.

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What challenges have you faced in data governance, and how did you address them?

Reflect on specific challenges related to data privacy, compliance, or quality assurance. Explain the steps you took to mitigate these challenges, whether through establishing protocols, refining practices, or improving stakeholder education.

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Tell me about a time you had to translate complex technical data for a non-technical audience.

Illustrate your ability to simplify technical jargon into understandable terms by providing a real-life example. Emphasize your communication skills and how you ensured that the audience left with a clear understanding of the data's implications.

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What are your thoughts on the future of data management and its implications for product management?

Convey your insights about emerging trends in data management, such as the importance of real-time analytics or the integration of AI-driven decision-making tools. Discuss how these trends may influence product management strategies and the importance of adapting to evolving technologies.

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DATE POSTED
December 23, 2024

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