Principal Product Manager, Data Products
New
US states: AZ, CA, CO, FL, GA, KY, MD, MI, MO, NJ, NV, NC, PA, SC, SD, TX, VA, WA, or WYFull-TimePrincipal
Salary not disclosed
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Job Details
- Experience
- 7+ years of experience with product management, product development, and product ownership in data-focused organizations, with proven experience serving as a Scrum Product Owner
- Required Skills
- AWSSQLHadoopMachine LearningAirflowSpark
Requirements
- A Bachelor's degree in Computer Science, Information Systems, Analytics, Statistics, Applied Math, or a related engineering field.
- 7+ years of experience with product management, product development, and product ownership in data-focused organizations, with proven experience serving as a Scrum Product Owner.
- Deep experience with people data, public records, or identity data ecosystems — including PII handling, data vendor evaluation, and familiarity with batch append or data-as-a-service (DaaS) product models.
- Demonstrated experience with entity resolution, record linkage, or identity graph products, with working knowledge of person-level matching challenges and familiarity with weakly supervised machine learning approaches to data quality improvement.
- Experience with SQL for profiling and analyzing data sets;
- Familiarity with open-source big-data tools such as AWS, Spark, Hadoop, or Airflow preferred.
- Excellent communication skills and attention to detail, with a track record of influencing without authority across technical and business stakeholders.
Responsibilities
- Own and prioritize a data development backlog and project delivery schedule to execute customer-focused roadmap deliverables, serving as Product Owner for an Agile Scrum team responsible for regular data builds that generate high-quality people profiles at scale.
- Work closely with developers, analysts, and architects to fully understand available data and define business logic, including cleaning and standardization requirements; lead efforts to evaluate and onboard new external data vendors providing people data and PII.
- Conduct and review data analysis, profiling, and mining using traditional statistical techniques to understand and strengthen data capabilities; define what data accuracy means for the company's data products and translate those standards into actionable engineering project plans.
- Document requirements by writing user stories that align with product needs; lead the product roadmap for entity resolution improvements using weakly supervised machine learning techniques in collaboration with data science and ML engineering teams.
- Collaborate with product and data stakeholders to gather requirements needed to develop aggregated data to support the product suite; lead strategic development and improvement of the batch append product offering.
- Define acceptance and data quality criteria and guide the agile Scrum team to meet them; curate data labels and drive their integration into the data build process to systematically improve data product quality.
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