DataOps/Cloud Data Engineer

Tasks

• Design and develop data pipelines from source to end user, including workflow orchestration, deployment, automation, and data provisioning.
• Build and support cloud and on-premises data platforms, storage, databases, data warehouses, data lakes, and lakehouses.
• Develop data solutions for structured, semi-structured, and unstructured data, including collection, ingestion, transformation, exchange, and operational support.
• Design data mappings, fact and dimension models, enterprise data warehouses, data lakes, and lakehouses.
• Support large-scale data conversion and migration from OLTP and OLAP environments to cloud services and platforms.
• Manage and optimize cloud data services such as storage, repositories, data lakes, lakehouses, Key Vault, virtual machines, and disks.
• Apply DataOps practices, Agile delivery, CI/CD, data provisioning automation, data security, monitoring, and performance tuning.

Requirements

• 8+ years of relevant data engineering experience.
• Design, build, automate, and optimize ETL/ELT pipelines using Databricks, PySpark, and Delta Live Tables (DLT) / Lakeflow Declarative Pipelines or equivalent.
• Develop unified data platforms using Databricks and Unity Catalog or an equivalent data catalog.
• Build Azure Data Factory pipelines, including copy activities and custom Databricks data pipelines.
• Implement CI/CD using Azure DevOps and Git integration.
• Strong SQL, relational and dimensional data modeling, query optimization, data replication, and database administration.
• Hands-on experience with one or more of Oracle, MySQL, or SQL Server, and PL/SQL or T-SQL.
• Data migration and integration experience across platforms, inc

Schedule

• Onsite

Location

• Toronto, Ontario