RQ08912 - Data Architect/Modeller - Senior at Rubicon Path – Toronto | Jobyssey

Responsibilities:

Construct a high-level overview of the entire data landscape of the organization.
Illustrate how data moves through the organization and between systems.
Develop high-level designs outlining the main entities and their relationships.
Design detailed models showing attributes, primary keys, and relationships between entities without considering physical aspects.
Implement designs showing how data will be stored, including tables, columns, indexes, and relationships.
Design diagrams showing how different data systems and databases interact and are integrated.
Document standards and policies for data management, including naming conventions, data quality standards, and data security policies.
Plan and guide the roles and responsibilities of data stewards in maintaining data quality and integrity.
Compile detailed descriptions of data elements, their meanings, and their relationships.
Create a comprehensive list of business terms and their definitions to ensure consistent usage across the organization.
Document and design processes for extracting, transforming, and loading data from various sources.
Strategize and schedule the movement of data from legacy systems to new systems or platforms.
Detail the design of the data warehouse, including the schema, dimensions, and fact tables.
Set up and configure BI tools and dashboards.
Regularly report on the quality of data, identifying issues and areas for improvement.
Develop strategies and methods for cleaning and improving the quality of data.
Plan and diagram how data security will be implemented and maintained.
Document compliance with relevant regulations and standards.
Develop strategies for improving the efficiency and performance of data systems.
Detail plans for data architecture projects, including timelines, milestones, and resources required.
Document technical specifications for all data architecture components and processes.

SkillsExperience and Skill Set Requirements

Public Sector Experience

· 5+ years of experience working with federal/provincial/broader public-sector healthcare providers.

· Knowledge of Public Sector Enterprise Architecture artifacts (or similar), processes and practices, and ability to produce technical documentation that comply with industry standard practices.

· In-depth knowledge of industry standard such as Project Management Institute (PMI) and Public Sector I&IT project management methodologies.

· Knowledge and experience with Public Sector Health related projects.

· Knowledge and understanding of Ministry policy and IT project approval processes and requirements.

· Experience adopting and adhering to Public Sector Unified I&IT Project Methodology, Public Sector Enterprise Architecture and Public Sector Gating process, and Public Sector Standard Systems Development Methodologies.

· Experience with large complex IT Health-related projects.

5 points

Technical Skills and Experience

7+years experiences in the following:

· developing conceptual, logical and physical data models for structured, semi-structured, and unstructured data with relational, star and snowflake schemas.

· Proficiency in data modeling methods and tools (e.g. ERWIN, VISIO, Power Designer).

· developing and implementing common data models and master data management strategies

· design schemas that balance agility, schema flexibility, data governance, and quality.

· Expertise in creating schemas that allow flexible querying and analysis across various data formats.

· defining data partitioning, clustering, and indexing strategies to optimize query performance and data access patterns.

· implementing schemas and metadata structures that support efficient data management.

· Understanding of data governance principles and practices, especially in designing schemas and metadata structures.

· Experience in creating Architecture Artefacts based on enterprise standards.

· 4+ years experience in designing schemas that integrate diverse data types stored in a data lake or data lakehouse.

· 3+ years experience of implementing Medallion architecture or similar frameworks. Familiarity with tools and techniques for managing metadata in a data lakehouse environment.

· Hands-on experience with Azure services, including Azure Data Factory, Azure Data Lake Storage, and Azure Databricks.

50 points

Core Skill and Experience

· 10+ years experience with Solutions development.

· Experience in addressing complex data integration challenges and design efficient, scalable data models.

· Experience in monitoring and enforcing data modelling/normalization standards.

· Experience with the privacy and security requirements or software development in a health context, or equivalent.

· Demonstrated knowledge of leading technical design, security and recovery procedures for application development.

· Experience with relational and hierarchical database technologies.

· Demonstrated understanding and experience with the use of information retrieval packages using query languages.

· Experience in production environment troubleshooting and tuning to improve performance.

· Knowledge and experience of Information Management tools, principles, concepts, policies and practices.

30 points

General Skills

· Experience with at least two different platforms, operating systems, environments, database technologies, languages and communications protocols.

· Knowledge of performance considerations for different database designs in different environments.

· Experience in structured methodologies for the design, development and implementation of applications.

· Experience in systems analysis and design in large or medium systems environments.

· Awareness of emerging I&IT trends and directions

· Excellent analytical, problem-solving and decision-making skills; A team player with a track record for meeting deadlines. Strong communication skills to articulate data architecture concepts and collaborate with stakeholders.

· Experience working with cross-functional teams, including IT, business, and data engineering teams.

· Strong analytical skills to understand and model complex data relationships and structures.

· Meticulous attention to detail in designing and implementing data models and schemas.

15 points

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