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Data Architect Specialist

Job in Dearborn, Wayne County, Michigan, 48120, USA
Listing for: KYYBA, Inc
Full Time position
Listed on 2026-06-05
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Business Systems/ Tech Analyst, Data Engineer
Job Description & How to Apply Below
We are seeking a Data Product Manager to define, develop, and manage data products that enable business insights, operational efficiency, and data-driven decision-making. The ideal candidate will bridge business, engineering, analytics, and data science teams to deliver scalable, high-quality data solutions aligned with organizational goals.

Required Qualifications
* Bachelor s degree in Computer Science, Information Systems, Engineering, Business, Data Analytics, or a related field.
* 5+ years of Product Management, Data Management, Business Intelligence, Analytics, or related experience.
* Strong understanding of data warehousing, data modeling, ETL/ELT processes, and cloud data platforms.
* Experience working with Agile methodologies and product management frameworks.
* Ability to translate complex technical concepts into business value.
* Strong stakeholder management, communication, and leadership skills.
* Experience defining KPIs, product metrics, and business cases.

Preferred Qualifications
* Master s degree in Business, Data Science, Analytics, or a related field.
* Experience with cloud platforms such as Amazon Web Services, Microsoft, or Google.
* Familiarity with SQL, Python, data visualization tools, and modern data architectures.
* Experience with data governance, master data management, and data catalog solutions.
* Experience leading enterprise-scale data transformation initiatives. Technical Skills
* Data Product Management
* Data Warehousing & Data Lakes
* Data Modeling
* SQL & Analytics
* Data Governance & Quality
* Cloud Data Platforms
* Agile/Scrum
* KPI & Metrics Development
* API and Data Services Management
* Stakeholder Management Success Metrics
* Data product adoption and user satisfaction
* Data quality and reliability improvements
* Reduction in data delivery lead times
* Business value generated through analytics and insights
* Stakeholder satisfaction and engagement
* Achievement of roadmap milestones and product objectives Typical Data Products
* Enterprise data platforms
* Customer 360 solutions
* Product analytics datasets
* Operational dashboards and reporting systems
* Machine learning feature stores
* Data APIs and self-service analytics platforms This description can be tailored further for specific industries such as automotive, healthcare, finance, retail, or manufacturing. Given your background in product lifecycle management and 3DX initiatives, I can also create a Data Product Manager job description focused on automotive digital engineering, PLM, and software-defined vehicle programs.

Skills Required:

Data Management

Skills Preferred:
Product Management

Experience

Required:

Specialist Exp.: 10+ yrs in IT; 4+ yrs in concentration

Experience Preferred:
0

Education Required:

Bachelor's Degree

Additional Information:
Hybrid Role Onsite 4 days a week

Key Responsibilities
* Define and own the vision, strategy, roadmap, and lifecycle of data products.
* Partner with business stakeholders to understand data needs and translate them into product requirements.
* Collaborate with data engineers, architects, analysts, and data scientists to design and deliver data products and platforms.
* Prioritize features, enhancements, and technical investments based on business value and customer impact.
* Establish and track key performance indicators (KPIs) for data product adoption, quality, and business outcomes.
* Drive data governance, metadata management, data quality, and compliance initiatives.
* Develop user stories, acceptance criteria, and product backlogs.
* Lead Agile ceremonies and coordinate cross-functional teams to ensure timely delivery.
* Gather feedback from users and stakeholders to continuously improve data products.
* Communicate product strategy, progress, and outcomes to leadership and stakeholders.
* Ensure data products support scalability, security, reliability, and regulatory requirements.
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