Principal Data Product Manager

Varmoda Tech

$130K — $155K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10 years of experience in Data Product Management.
  • Minimum of 10 years leading data product initiatives in the PBM space.
  • Strong expertise in data integration, transformation, and standardization.
  • Proven ability to define and execute complex integration roadmaps.
  • Exceptional communication skills across organizational levels.
  • Bachelor's Degree in related fields or equivalent experience.

Responsibilities

  • Develop and maintain the Data Product Vision, Strategy, and Roadmap.
  • Define success metrics and prioritize enhancement requests.
  • Translate customer needs into data platform requirements.
  • Lead the development of data and analytics products with Data Directors.
  • Oversee the deployment of the enterprise's data and analytics platform.
  • Collaborate with cross-functional teams to achieve goals.
  • Assess competitors' data offerings and identify market opportunities.

Benefits

  • Flexible work arrangements.
  • Opportunities for professional development.
  • Access to cutting-edge data technologies.
  • Supportive and collaborative work culture.
Full Job Description
Position summary

Varmoda is seeking a Principal Data Product Manager responsible for managing the entire lifecycle of enterprise data products and services to align with company goals. The role will lead the strategic direction of data products and coordinate teams of business leaders, data engineers, data architects, data analysts, and data scientists. The Data Product Manager will establish and execute the data product operating model, define the vision and strategy for data products, implement product management processes, and produce roadmaps for high-quality, high-performing data products.

Key Responsibilities
  • Develop and maintain the Data Product Vision, Strategy, and Roadmap with input from various stakeholders.
  • Define success metrics and strategic priorities, partner on enhancement requests, and prioritize them.
  • Work with customers and internal stakeholders to understand and translate their needs into data platform requirements.
  • Utilize enterprise information assets and analytics for decision-making and regulatory reporting.
  • Lead the development of data and analytics products with Data Directors and Data Product Managers.
  • Oversee deploying the enterprise's data and analytics platform, ensuring quality, traceability, timeliness, usability, and cost-effectiveness.
  • Collaborate with Data Directors, Data Product Managers, and SMEs to finalize data requirements.
  • Work with the engineering team through planning and iteration.
  • Lead cross-functional teams to achieve departmental, divisional, and enterprise goals.
  • Promote data capabilities internally and externally.
  • Assess competitors' data offerings and identify market opportunities.
  • Assist with customer communications and scan for emerging data management strategies, tools, and technologies.
  • Create value from the organization's data assets and enable internal/external analytics and insights.
  • Develop strategies to achieve business outcomes, drive innovation, and ensure compliance with regulatory, legal, and ethical requirements.
  • Collaborate with customers, business stakeholders, data architects, data scientists, data engineers, and product owners to build the data foundation for the data product catalog.
  • Gather requirements, write use cases, organize features, implement tools, and establish metrics for managing the data product lifecycle and maintaining a data product catalog or subscription.
  • Oversee data integration, data ingestion, data transformation, and data standardization with third-party PBM systems.
  • Define and execute complex integration roadmaps and support data flow, ingestion, and integration across data platforms and ecosystems.
  • Work with Snowflake, Kafka topics, ETL, and related data platform technologies.
  • Handle tasks at the ground level while overseeing the overall data product.

Required Qualifications
  • 10 years of experience in Data Product Management.
  • Minimum of 10 years of experience leading data product initiatives within the PBM space, with a deep understanding of PBM operations, data ecosystems, business processes, and integration challenges.
  • Strong expertise in data integration, data transformation, data standardization, and enterprise data platforms.
  • Proven ability to define and execute complex integration roadmaps.
  • Strong technical understanding to translate and deliver the needs of the business and work with technical team members.
  • Strong understanding and experience with data platforms and data ecosystems.
  • Solid understanding and experience with data flow, ingestion, and integration of data platforms.
  • Exceptional communication skills with the ability to engage effectively at every level of the organization-from CEO and executive leadership teams to architects, engineers, and operational stakeholders.
  • Ability to motivate and influence others so that project objectives are met in a timely manner.
  • Ability to collaborate with stakeholders to develop high quality solutions.
  • Ability to coach, delegate, and develop architects and engineers.
  • Ability to manage cross-domain architecture solutions and issues.
  • Expertise with domain related architecture frameworks, methods and tools.
  • Effective organizational, interpersonal/relationship management, analytical, communications (written and verbal), and collaboration skills.
  • Bachelor's Degree in business administration, finance, computer science, data science, engineering, information science, related fields, or equivalent work experience.

Preferred Qualifications
  • Advanced degree.
  • Recent experience with PBM systems and processes.
  • Experience with third-party PBM data integration and ingestion.
  • Experience with Snowflake, Kafka topics, and ETL.
  • Experience managing enterprise data platforms and data ecosystems.
  • Experience working across business, architecture, engineering, analytics, and data science teams.
  • Experience with emerging data management strategies, tools, and technologies.

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