Data Architect

Ex; Chicago (IL); On-site; USD 110,000 - 170,000; Full time

Job summary

Ex in Chicago seeks a Data Architect to design, develop, and maintain enterprise data models and solutions. You will translate business needs into robust data architecture, support data movement, and ensure data quality across platforms.

The role collaborates with application development teams to build data flows, maintain metadata, and enforce standard naming conventions. You will be responsible for versioning documentation and models to ensure consistent delivery between client and team.

Qualifications

• Translate business needs into data models and architecture for long-term solutions.
• Develop best practices for data naming conventions and data governance.
• Collaborate with development teams to implement data strategies and data flows.

Responsibilities

• Understand and translate business needs into data models and architecture.
• Work with development teams to implement data strategies and data flows.
• Create and maintain conceptual, logical, and physical data models with metadata.
• Optimise data models to support new and existing projects.
• Develop best practices for naming conventions and coding practices.
• Organise documentation and models with version control for clear delivery.

Skills

Data modelling

Data architecture

Data flows

Metadata

Version control

Job description

The Data Architect will provide technical expertise in analysis, design, development, rollout and maintenance of enterprise data models and solutions
Provides technical expertise in needs identification, data modelling, data movement and transformation mapping (source to target), automation and testing strategies, translating business needs into technical solutions with adherence to established data guidelines and approaches from a business unit or project perspective.

Essential Duties

• Understand and translate business needs into data models and data architecture supporting long-term solutions.
• Work with the Application Development team to implement data strategies, build data flows and development of data models.
• Create and maintain conceptual, logical, and physical data models using best practices to ensure high data quality and reduced redundancy, along with corresponding metadata.
• Optimise and update logical and physical data models to support new and existing projects.
• Develop best practices for standard naming conventions and coding practices to ensure consistency of data models.
• Organized and rigorous with versioning of documentation and models to ensure consistent delivery and understanding between the client and development team.
• Recommend opportunities for reuse of data models in new environments.
• Perform reverse engineering of physical data models from databases and SQL scripts.

Evaluate data models and physical databases for variances and discrepancies.