Description

In this role, you will lead the strategy, roadmap, and execution of significant data product initiatives designed to transform legacy systems into scalable, high-value assets. You will partner across data engineering, data science, analytics, and business teams to mature data practices, migrate to modern data platforms, and enable better decision-making and operational efficiency across the enterprise.

Responsibilities

• Define vision and roadmap for data products, including data platforms, analytics tools, and ML infrastructure.
• Identify high-value opportunities by investigating the data landscape, pain points, and business needs.
• Align data product strategy with organizational priorities and long-term data architecture in partnership with Enterprise Architecture and stakeholders.
• Connect data capabilities to business outcomes and organize efforts to achieve measurable results.
• Lead the end-to-end lifecycle of data products: requirements, design, development, testing, launch, and iteration.
• Partner with data engineers and data scientists to build scalable pipelines, models, and data services while ensuring data quality, governance, lineage, and documentation standards.
• Translate business logic into data transformations, metadata, and domain-specific rules.
• Serve as the primary liaison between technical teams and business partners, communicating product value, roadmap, and use cases to leadership and cross-functional teams.
• Prioritize incoming requests and balance competing needs across teams.
• Define success metrics and measure product performance and adoption.
• Ensure data products deliver actionable insights and support decision-making across the organization.
• Partner with analytics teams to design dashboards, KPIs, and reporting frameworks.
• Uphold data governance, privacy, and ethical AI standards; ensure compliance with regulatory and organizational data policies.
• Advocate for responsible data use.
• Provide knowledge transfer to support organizational continuity.

Qualifications

• Required
  • 4–7+ years of experience in data management, data analytics, data engineering, or related fields.
  • Demonstrated product leadership skills and ability to work in ambiguity.
  • Strong understanding of data systems including pipelines, warehousing, modeling, metadata, and governance.
  • Proficiency collaborating with data architecture, data engineering, and data science teams.
  • Ability to translate complex technical concepts into business-friendly language.
  • Strong communication, prioritization, and stakeholder management skills.
  • Experience with SQL, data lakes, and data pipelines/ETL.
  • Understanding of large organizational data sharing constraints and data sharing agreements.
• Preferred
  • Experience with analytics tools such as dbt, Looker, Tableau, Power BI, or Google Analytics.
  • Significant experience with Databricks.
  • Familiarity with Java and Python.
  • Background in building internal platforms or developer-facing products.
  • Experience implementing modern data architectures at an organization.
  • Experience in a highly regulated industry performing statistical analysis and reporting

Key Skills

Education

Any Graduate