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As a Technical Product Owner, you will define and execute the product vision and strategy, lead the end-to-end lifecycle of data warehouse solutions (ideation through sustainment), and identify improvement opportunities. You will manage enterprise business data projects as it relates to functionality, design, and features. You will define and execute detailed roadmaps and product priorities based on a solid understanding of business needs and data engineering. The Data Product Owner will influence, educate, and prioritize the data warehouse and analytics requirements backlog as well as the strategic decisions to enable the next slate of outstanding experiences for our customers.


Responsibilities 

  • Maintaining a prioritized product backlog for the data technologies scrum teams. 
  • Work with cross-departmental business partners, Data/BI engineers and own the end to end delivery of the data warehouse platform improvements, which includes documenting and prioritizing user stories, demoing solution designs, testing and releasing changes into a Production Data Warehouse environment.
  • Be a strategic partner and work with business stakeholders to define high impact analytical problems and find innovative ways to solve problems with data 
  • Define and own overall product vision, strategy, and success metrics for key initiatives around data warehouse and business intelligence. 
  • Capture and analyze requests from teams across Finance, Marketing, Sales, Product, and other teams to define data needs and prioritize roadmap.
  • Collaborate with Business Analysts, cross-functional product owners  and data/BI engineers to craft solutions and present business cases to the broader teams. 

Requirements:

  • 12+ years of professional experience working in an Enterprise Data Warehouse and Business Intelligence Product, Technical Product, or Technical/Engineering role. 
  • Proven track record working directly with business application teams (such as SFDC, SAP, Workday and other SaaS applications) and Data Warehouse systems as a product owner interfacing directly with data engineering teams in a high scale environment.
  • Experience with Data Warehouse Techniques (Data Modeling, ETL, Database systems, Business Intelligence) in SaaS stack such as Snowflake, Tableau, etc.
  • Exposure to SaaS business applications such as SFDC, SAP, Workday, Gainsight, etc. 
  • Strong SQL query experience (must be able to analyze large,complex data sets).
  • Familiar with PM methodologies (e.g., Agile, Kanban, etc.) and knowledge of when to apply methodologies. 
  • Ability to communicate persuasive discussions, write clearly and concisely, listen attentively, and collaborate with partners to reach mutually beneficial outcomes 
  • Collaborative team player, with strong communication skills, including the ability to translate complex technical products and features into simple concepts and presentations
 
 
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Splunk turns machine data into answers. Organizations use market-leading Splunk solutions with machine learning to solve their toughest IT, Internet of Things and security challenges.
 
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