Data Architect

Requirement Details:

Job Title: Data Architect Senior Specialist

Location: Dearborn, Michigan.

Duration: Full-time

Skills Required: Power Builder, PostgreSQL, GCP, Big Query,

Description:

Experience Required: 10 years

Work Status: 4 days Onsite

"Position Description:

Hybrid with on-site 4 days/week (per the client guidelines) Employees in this job function are responsible for designing, building and maintaining reliable, efficient and scalable data architecture and data models that serve as a foundation for all data solutions. They also closely collaborate with senior leadership and IT teams to ensure alignment of data strategy with overall business goals. Key Responsibilities: 1) Align data strategy to business goals to support a mix of business strategy, improved decision-making, operations efficiency and risk management 2) 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 3) Design and build reliable, efficient and scalable data architecture to be used by the organization for all data solutions 4) Implement and maintain scalable architectural data patterns, solutions and tooling to support business strategy 5) Design, build, and launch shared data services and APIs to support and expose data-driven solutions in line with enterprise architecture standards 6) Research and optimize data architecture technologies to enhance and support enterprise technology and data strategy

Skills Required:

Power Builder, PostgreSQL, GCP, Big Query

Skills Preferred:

N/A

Experience Required:

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

Experience Preferred:

1) Must have experience presenting technical material to business users 2) Must be able to envision larger strategies and anticipate where possible synergies can be realized 3) Experience acting as the voice of the architecture/data model and defend its relevancy to ensure adherence to its principles and purpose

Education Required:

Bachelor's Degree

Education Preferred:

Additional Safety Training/Licensing/Personal Protection Requirements:

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."