Lead Software Engineer
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- Years of Experience: 5-7 Years
- Posting language
- English
- Posted
Original job description
Data Architect
Location: PCS CA~TORONTO
Years of Experience: 5-7 Years
Job Summary: We are seeking a strategic Data Architect to define and implement enterprise data architecture that aligns with business objectives and supports digital transformation initiatives. This role is crucial in ensuring that data assets are structured, integrated, and optimized for analytics, reporting, and operational efficiency. The Data Architect will collaborate with business stakeholders, IT leadership, and engineering teams to design scalable, secure, and high-performing data ecosystems that enable data-driven decision-making across the organization.
Responsibilities
Location: PCS CA~TORONTO
Years of Experience: 5-7 Years
Job Summary: We are seeking a strategic Data Architect to define and implement enterprise data architecture that aligns with business objectives and supports digital transformation initiatives. This role is crucial in ensuring that data assets are structured, integrated, and optimized for analytics, reporting, and operational efficiency. The Data Architect will collaborate with business stakeholders, IT leadership, and engineering teams to design scalable, secure, and high-performing data ecosystems that enable data-driven decision-making across the organization.
Responsibilities
- Develop and maintain enterprise data architecture frameworks aligned with business goals.
- Design end-to-end data pipelines and integration strategies using modern cloud technologies.
- Define data modeling standards, metadata management, and governance principles.
- Collaborate with business analysts and data engineers to translate requirements into technical designs.
- Ensure data quality, consistency, and compliance with regulatory standards.
- Optimize data storage, retrieval, and transformation processes for performance and scalability.
- Lead architecture reviews and provide guidance on data platform enhancements.
- Evaluate emerging technologies and recommend adoption strategies for data modernization.
- AWS Glue - Expert
- PySpark - Expert
- Data Modeling (Conceptual, Logical, Physical) - Expert
- Cloud Data Architecture (AWS ecosystem) - Expert
- Data Governance & Metadata Management - Advanced
- SQL and NoSQL Databases - Advanced
- Data Lake & Warehouse Design (Redshift, Snowflake) - Advanced
- ETL/ELT Frameworks & Automation - Advanced
- Good Communication
- Stakeholder Management
- Agile Methodology
- Documentation & Standards
- Problem Solving & Analytical Thinking
- Data Security & Compliance Awareness
- Leadership & Mentoring
More about this job
Responsibilities
Develop enterprise data architecture and scalable data pipelines that support business goals, analytics, reporting, and operational efficiency. Establish data modeling, governance, metadata, quality, and compliance standards while guiding architecture reviews and evaluating modernization technologies.
Requirements
Requires 5–7 years of experience and expert-level skills in AWS Glue, PySpark, data modeling, and AWS cloud data architecture, along with advanced data governance, databases, data lake and warehouse design, and ETL/ELT. A bachelor's degree in computer science, information technology, or a related field is required; relevant certifications are a plus.
Skills
- AWS Glue
- PySpark
- Data Modeling
- AWS Cloud Data Architecture
- Data Governance
- Metadata Management
- SQL
- NoSQL Databases
- Data Lake Design
- Data Warehouse Design
- Redshift
- Snowflake
- ETL/ELT
- Data Pipelines
- Data Security and Compliance
- Stakeholder Management
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Management & Leadership
Keywords
- Data Architecture
- Enterprise Data Architecture
- AWS Glue
- PySpark
- AWS
- Data Modeling
- Conceptual Data Models
- Logical Data Models
- Physical Data Models
- Cloud Data Architecture
- Data Governance
- Metadata Management
- SQL
- NoSQL
- Data Lakes
- Data Warehouses
- Amazon Redshift
- Snowflake
- ETL
- ELT
- Data Pipelines
- Data Integration
- Data Quality
- Data Security
- Regulatory Compliance
- Analytics
- Digital Transformation
- Agile Methodology
- Stakeholder Management
- Data Modernization