Senior Data Architect with GCP

Role: Senior Data Architect with GCP (W2 Position)

Location: Dearborn MI (Hybrid)

Duration: 12 Months

Experience: 10 Years

Job Description:

Key Responsibilities:

• Align data strategy to business goals to support a mix of business strategy improved decision-making operations efficiency and risk management
• Ensure data assets are available consumable and secure for end users across the enterprise applications platforms and infrastructure within the confines of enterprise and security architecture
• Design and build reliable efficient and scalable data architecture to be used by the organization for all data solutions
• Implement and maintain scalable architectural data patterns solutions and tooling to support business strategy
• Design build and launch shared data services and APIs to support and expose data-driven solutions in line with enterprise architecture standards
• Research and optimize data architecture technologies to enhance and support enterprise technology and data strategy

Skills Required:

Power Builder PostgreSQL GCP Big Query

Experience Required:

Senior Specialist Exp.: 10 years in IT; 7 years in concentration

Experience Preferred:

• Must have experience presenting technical material to business users
• Must be able to envision larger strategies and anticipate where possible synergies can be realized
• Experience acting as the voice of the architecture/data model and defend its relevancy to ensure adherence to its principles and purpose

Education Required:

Bachelors Degree

Additional Information :

• Data Modeling and Design: Develop conceptual logical and physical data models for business intelligence analytics and reporting solutions. Transform requirements into scalable flexible and efficient data structures that can support advanced analytics.
• Requirement Analysis: Collaborate with business analysts stakeholders and subject matter experts to gather and interpret requirements for new data initiatives. Translate business questions into data models that can answer these questions.
• Data Integration: Work closely with data engineers to integrate data from multiple sources ensuring consistency accuracy and reliability. Map data flows and document relationships between datasets.
• Database Architecture: Design and optimize database schemas using the medallion architecture which includes relational star schema and denormalized data sets for BI and ML data consumers.
• Metadata Management: Team with the data governance team so detailed documentation on data definitions data lineage and data quality statistics are available to data consumers.
• Data Quality Assurance: Establish master data management data modeling so the history of how customer provider and other party data is consolidated into a single version of the truth.
• Collaboration and Communication: Serve as a bridge between technical teams and business units clearly communicating the value and limitations of various data sources and structures.
• Continuous Improvement: Stay abreast of emerging trends in data modeling analytics platforms and big data technologies. Recommend enhancements to existing data models and approaches.
• Performance Optimization: Monitor and optimize data models for query performance and scalability. Troubleshoot and resolve performance bottlenecks in collaboration with database administrators.
• Governance and Compliance: Ensure that data models and processes adhere to regulatory standards and organizational policies regarding privacy access and security.