Data Architect

2 months ago

Toronto, Ontario, Canada Cpus Engineering Staffing Solutions Inc. Full time
Job Title: Data Architect

About the Role:

We are seeking a highly skilled Data Architect to join our team at Cpus Engineering Staffing Solutions Inc. as a key member of our data engineering team. The successful candidate will be responsible for designing, implementing, and maintaining large-scale data architectures that support our business operations.

Key Responsibilities:

  • Design and Implement Data Architectures: Lead the architecture, design, and implementation of modular and scalable data ELT/ETL pipelines and data infrastructure leveraging a wide range of data sources across the organization.
  • Develop Data Models: Design curated common data models that offer an integrated, business-centric single source of truth for business intelligence, reporting, and downstream system use.
  • Ensure Data Security: Work closely with infrastructure and cyber teams to ensure data is secure in transit and at rest.
  • Develop Code Templates: Create, guide, and enforce code templates for delivery of data pipelines and transformations for structured, semi-structured, and unstructured data sets.
  • Establish Modeling Guidelines: Develop modeling guidelines that ensure model extensibility and reuse by employing industry-standard disciplines for building facts, dimensions, bridge, aggregates, slowly changing dimensions, and other dimensional and fact optimizations.
  • Transform Data: Transform data and map to more valuable and understandable semantic layer sets for consumption, transitioning from system-centric language to business-centric language.
  • Collaborate with Teams: Collaborate with business analysts, data scientists, data engineers, data analysts, and solution architects to develop data pipelines to feed our data marketplace.
  • Introduce New Technologies: Introduce new technologies to the environment through research and POCs and prepare POC code designs that can be implemented and productionized by developers.
  • Work with Microsoft Stack: Work with tools in the Microsoft Stack; Azure Data Factory, Azure Data Lake, Azure SQL Databases, Azure Data Warehouse, Azure Synapse Analytics Services, Azure Databricks, Microsoft Purview, and Power BI.
  • Agile SCRUM Work Management: Work within the agile SCRUM work management framework in delivery of products and services, including contributing to feature & user story backlog item development, and utilizing related Kanban/SCRUM toolsets.
  • Document Architecture: Document as-built architecture and designs within the product description.
  • Design Data Solutions: Design data solutions that enable batch, near-real-time, event-driven, and/or streaming approaches depending on business requirements.
  • Orchestrate Data Pipeline Execution: Design and advise on orchestration of data pipeline execution to ensure data products meet customer latency expectations, dependencies are managed, and datasets are as up to date as possible, with minimal disruption to end-customer use.
  • Ensure Data Security and Access Management: Ensure that designs are implemented with proper attention to data security, access management, and data cataloging requirements.
  • Approve Pull Requests: Approve pull requests related to production deployments.
  • Demonstrate Solutions: Demonstrate solutions to business customers to ensure customer acceptance and solicit feedback to drive iterative improvements.
  • Troubleshoot Issues: Assist in troubleshooting issues for datasets produced by the team (Tier 3 support), on an as-required basis.
  • Guide Data Modelers: Guide data modelers, business analysts, and data scientists in the build of models optimized for KPI delivery, actionable feedback/writeback to operational systems, and enhancing the predictability of machine learning models and experiments.

Qualifications:

  • Education: 4-year university education in computer science, software engineering, or other relevant programs within data engineering, data analysis, artificial intelligence, or machine learning.
  • Experience: Minimum experience of +6 years and up to and including 8 years of experience is required in data modeling, data warehouse design, and data solution architecture in a Big Data environment is considered necessary.
  • Guiding Data Lake Ingestion and Modeling Projects: Experience guiding data lake ingestion and data modeling projects in a cloud environment, experience in modeling relational and in-memory models with star/snowflake schemas.
  • Designing and Implementing Event-Driven Solutions: Experience with designing and implementing event-driven (pub/sub), near-real-time, or streaming data solutions, involving structured, semi-structured, and unstructured data across various platforms.
  • Extensive Knowledge in Designing Data Models: Requires an extensive knowledge in designing a data model to solve a business problem, specifying a data pipeline design pattern to bring data into a data warehouse, optimizing data structures to achieve required performance, designing low-latency and/or event-driven patterns of data processing, creation of a common data model to support current and future business needs.

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