Data Architect

• At Prevalent we build Data Platforms that support Security Data Science for our clients

• This platform is highly complex; it brings together a large volume and variety of data by using modern big data and open-source technologies
• Due to the complex nature of the platform, it is important that the structure and meaning applied to the data is done in the right way
• To fulfill this challenge, we are looking for an experienced Data Architect who can support us with our journey
• This role is highly collaborative and will interact effectively with various internal stakeholders
• It is essential to have a broad understanding of various relevant technologies, with deep expertise to be hands-on with some of them
• The ideal candidate would also be a self-starter and self-motivated individual with a strong commitment to quality, a positive work ethic, and a "can do" attitude

The key accountabilities for this role:

• Analyze and translate business needs into long-term solution data models.
• Work with the development team to create conceptual data models and data flows.
• Develop best practices for data coding to ensure consistency within the system.
• Troubleshoot and optimize data systems
• Drive metadata capture through data modeling application
• Drive the design and implementation of data governance practices within the organization
• Drive design of data structures
• Lead management and version control of data models
• Create and optimize data structures for reporting and data integration
• Recommend and implement design and maintenance standards, guidelines, and procedures Ensure appropriate documentation is created, reviewed, published, and maintained.
• Coach and mentor, the team on Data Architecture Best Practices

Skills & Experience:

• Hands-on experience with conceptual and logical data modeling.
• Experience in data modeling, data warehousing, data entity analysis, conceptual, logical and physical model development in relational database environments
• Significant experience working on Data Modelling tools like Erwin, Hackolade, etc.
• Experience with data modelling methodologies like Kimball, Inmon and Data Vault
• Experience with graph data modelling
• Experience with data modelling on modern data stack like databricks, snowflake, synapse, neo4j, etc.
• Good understanding of reference data, masterdata, metadata, ontologies and taxonomies
• Ability to communicate with and present to audiences of different participants (e.g., executives, clients, technical peers, non-technical professionals) and size.
• Excellent consultative, facilitative, and consensus-building abilities
• Excellent analytical, data profiling, and problem-solving abilities
• Strong interpersonal skills.
• Excellent communication and presentation skills.

Knowledge:

• Knowledge of metadata management and related tools.
• Knowledge of mathematical foundations and statistical analysis.
• Solid understanding of transaction and information systems
• Advanced SQL knowledge
• Proficiency in industry-standard data modelling methodologies

Education:

• Masters / Degree in Engineering preferably Computer Science