Specialist Data Architect

Role Description

The role is responsible for developing and maintaining the data architecture across Data analytics platforms and applications, along with liaising with Architecture that includes the activities required for data flow design, data modelling, physical data design, query performance optimization.

The Data Modeler architect position is responsible for developing business information models by studying the business, our data, and the industry. This role involves creating data models to realize a connected data ecosystem that empowers consumers. The Data Modeler architect drives cross-functional data interoperability, enables efficient decision-making, and supports AI usage of Foundational Data.

Roles Responsibilities

• Develop and maintain conceptual logical, and physical data models and to support business needs
• Contribute to and Enforce data standards, governance policies, and best practices
• Design and manage metadata structures to enhance information retrieval and usability
• Maintain comprehensive documentation of the architecture, including principles, standards, and models
• Evaluate and recommend technologies and tools that best fit the solution requirements
• Drive continuous improvement in the architecture by identifying opportunities for innovation and efficiency

Basic Qualifications and Experience

• Masters degree with 4 - 6 years of experience in Computer Science, IT or related field OR
• Bachelors degree with 6 - 8 years of experience in Computer Science, IT or related field OR
• Diploma with 10 - 12 years of experience in Computer Science, IT or related field

Functional Skills

Must-Have Skills

• Data Modeling: Proficiency in creating conceptual, logical, and physical data models to represent information structures.
• Ability to interview and communicate with business Subject Matter experts to develop data models that are useful for their analysis needs.
• Metadata Management: Knowledge of metadata standards, taxonomies, and ontologies to ensure data consistency and quality.
• Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), performance tuning on big data processing
• Implementing Data testing and data quality strategies.

Good-to-Have Skills

Good-to-Have Skills:

• Experience with Graph technologies such as Stardog, Allegrograph, Marklogic

Professional Certifications

• Certifications in Databricks are desired

Soft Skills

• Excellent critical-thinking and problem-solving skills
• Strong communication and collaboration skills
• Demonstrated awareness of how to function in a team setting
• Demonstrated awareness of presentation skills