Data Product Owner

6 days ago

Glendale, Arizona, United States INSPYR Solutions Full time
Job Title: Data Product Owner - Enterprise

INSPYR Solutions is seeking an experienced Data Product Owner to lead the effort to create datasets, reports, and web applications used by the marketing and production teams.

Job Summary:

The Data Product Owner will work with an agile team of data and reporting engineers and provide both roadmap direction and day-to-day oversight. Our team is focused on empowering analysts, data scientists, and operations to make data-driven decisions, and this role will help us meaningfully further that mission.

Responsibilities:
  • Coordinate the ingestion, aggregation, and materialization of small-to-medium-to-very-big tables used by data analysts and scientists
  • Lead the design and development of data visualizations, dashboards, and custom web applications
  • Create and socialize team roadmaps internally and with key stakeholders
  • Foster collaboration between engineering and business units
  • Audit and evaluate our existing reports and BI systems usage for best practices and optimization opportunities
Platform Strategy & Roadmap:

The Data Product Owner will define the vision, strategy, and roadmap for the data platform based on business priorities, technical scalability, and security requirements.

Platform Optimization:

The Data Product Owner will work closely with the data team to design and implement new features, identify opportunities to automate tasks, leverage technology, and streamline the delivery of data.

Team Management:

The Data Product Owner will work closely with specialized scrum teams focused on business insights and machine learning, managing other product managers and dev/ops personnel, onboarding and mentoring new team members, and fostering a culture of innovation and accountability.

Stakeholder Management:

The Data Product Owner will act as a liaison between engineering, business units, and executive leadership, maintaining alignment with other product managers across the organization, and analyzing feedback from users to improve our platform offerings.

Product Oversight:

The Data Product Owner will oversee the lifecycle of platform development, from concept to deployment, ensuring alignment with business goals and technical specifications.

Collaboration:

The Data Product Owner will work closely with executive leadership, data scientists, engineers, and analysts to ensure accurate data collection, modeling, and insights generation, while maintaining strong partnerships across various teams.

Vendor & Stakeholder Management:

The Data Product Owner will manage relationships with key software vendors, such as Databricks, and oversee the consultants team to ensure projects are delivered successfully.

Systems Integration:

The Data Product Owner will product lead the evaluation, integration, and deployment of new data systems, including Alation, Tableau Cloud, Dataiku, SecuiPi, Immuta, Neo4j, as well as internally developed applications.

Data Governance & Compliance:

The Data Product Owner will ensure the reliability, quality, and governance of data platforms, aligning with industry best practices and compliance regulations.

Qualification:

Over seven years of experience in the data technology industry, primarily in roles focused on data engagement-from interpreting data to its precise application for business objectives.

Adept at distilling precise requirements from vague business demands, and guiding product discovery.

Ability to clearly communicate with executive-level stakeholders.

Experience with data: statistics, data cleansing, and data wrangling.

Scripting languages (i.e. Python, R) and big data technologies (i.e. Databricks, Snowflake) are a huge plus.

Experience working with major data visualization or business intelligence tools: Tableau, PowerBI, etc.

Advanced or expert SQL programming.

Comfortable designing data schemas, writing user stories, and fabricating test data sets with 7+ years of relevant experience.

Bachelor's or Master's degree in Data Science, Computer Science, Information Technology, Business, or a related field.

Familiarity with data warehouse and data lake platforms such as Snowflake and Databricks, along with a foundational understanding of their operations.

Strong understanding of data modeling, data architecture, and data warehousing principles.

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