Data Architect / Technical Architect
- Toronto, ON, Canada
Full-time
Applications open in a new tab.
Job details
- Job type
- Full-time
- Apply by
- Experience
- 10+ years of Data Architecture/Data Warehousing experience.
- Posting language
- English
- Posted
Original job description
Position: Data Architect / Technical Architect
Location: Toronto, ON (Hybrid)
Employment Type: Full Time
Experience Required: 10 + Years
Role Summary:
We are hiring a Data Architect /Technical Architect to lead the design and implementation of an enterprise-scale data platform using Databricks, Delta Lake, Snowflake, Azure, and SQL Server. The ideal candidate will have strong expertise in Data Warehousing, Kimball Modeling, Medallion Architecture, and large-scale data integration.
Key Responsibilities:
- Design and implement Bronze, Silver, Gold (Medallion) data architecture.
- Create scalable Fact & Dimension models, Star Schemas, and SCD Type I/II solutions.
- Develop ingestion frameworks for Snowflake, APIs, flat files, and vendor data sources.
- Establish data quality, audit, reconciliation, watermarking, and recovery strategies.
- Optimize Databricks/Delta Lake solutions for performance, scalability, and cost efficiency.
- Collaborate with business and engineering teams to deliver reporting and analytics solutions.
Required Skills:
- 10+ years of Data Architecture/Data Warehousing experience.
- Strong hands-on experience with Databricks, Delta Lake, PySpark, Spark SQL, and T-SQL.
- Expertise in Kimball Dimensional Modeling, Star Schema Design, Fact & Dimension Modeling.
- Experience with Snowflake, SQL Server, Azure Data Factory (ADF), Azure SQL, and REST APIs.
- Strong knowledge of data integrity, validation, reconciliation, and batch processing.
- Experience building high-volume data pipelines and modern analytics platforms.
Preferred Skills:
- Experience with Genesys Cloud, Verint, Contact Center Analytics, or Telephony Data.
- Knowledge of enterprise migration and parallel-run strategies.
More about this job
Responsibilities
Design and implement an enterprise-scale Medallion data platform, including scalable fact and dimension models, ingestion frameworks, and data quality, audit, reconciliation, watermarking, and recovery strategies. Optimize Databricks and Delta Lake solutions for performance, scalability, and cost, and collaborate with business and engineering teams to deliver reporting and analytics.
Requirements
Requires 10+ years of data architecture or data warehousing experience, with hands-on expertise in Databricks, Delta Lake, PySpark, Spark SQL, and T-SQL. Candidates should also have experience with dimensional modeling, Snowflake, SQL Server, Azure data services, REST APIs, high-volume pipelines, and data validation; contact center data and migration strategies are preferred.
Skills
- Data Architecture
- Data Warehousing
- Databricks
- Delta Lake
- PySpark
- Spark SQL
- T-SQL
- Kimball Dimensional Modeling
- Star Schema Design
- Snowflake
- SQL Server
- Azure Data Factory
- Azure SQL
- REST APIs
- Data Integration
- Medallion Architecture
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Consulting
Keywords
- Data Architecture
- Technical Architecture
- Data Warehousing
- Databricks
- Delta Lake
- Snowflake
- Azure
- SQL Server
- Kimball Modeling
- Medallion Architecture
- Bronze-Silver-Gold Architecture
- Dimensional Modeling
- Star Schema
- Fact and Dimension Modeling
- SCD Type I and II
- PySpark
- Spark SQL
- T-SQL
- Azure Data Factory
- Azure SQL
- REST APIs
- Data Ingestion
- Data Quality
- Data Integrity
- Reconciliation
- Batch Processing
- High-Volume Data Pipelines
- Contact Center Analytics
- Genesys Cloud
- Verint