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RQ08912 - Data Architect/Modeller - Senior

Rubicon Path638 open roles

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Toronto, Ontario, Canada
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Your applicationOpen nowRQ08912 - Data Architect/Modeller - SeniorRubicon Path · Toronto, Ontario, Canada
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Share of postings closed within
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  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 3 days ago

The posting

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

MUST HAVES:

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

· 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.

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