Data Science Developer - Senior

Must Haves:
5+ years experience Azure environment
5+ years experience Data engineering with ADF and Databricks
5+ years experience Programming experience with Python, SQL

Location:

3 days onsite Downtown Toronto
Responsibilities   Participate in product teams to analyze systems requirements, architect, design, code and implement cloud-based data and analytics products that conform to standards
Design, create, and maintain cloud-based data lake and lakehouse structures, automated data pipelines, analytics models
Liaises with cluster IT colleagues to implement products, conduct reviews, resolve operational problems, and support business partners in effective use of cloud-based data and analytics products.
Analyze complex technical issues, identify alternatives and recommend solutions.
Support the migration of legacy data pipelines from Azure Synapse Analytics and Azure Data Factory (including stored procedures, views used by BI teams, and Parquet files in Azure Data Lake Storage (ADLS)) to modernized Databricks-based solutions leveraging Delta Lake and native orchestration capabilities
Support the development of standards and a reusable framework that streamlines pipeline creation
Participate in code reviews and prepare/conduct knowledge transfer to maintain code quality, promote team knowledge sharing, and enforce development standards across collaborative data projects.
General Skills   Experience in multiple cloud-based data and analytics platforms and coding/programming/scripting tools to create, maintain, support and operate cloud-based data and analytics products, with a preference for Microsoft Azure

Experience with designing, creating and maintaining cloud-based data lake and lakehouse structures, automated data pipelines, analytics models in real world implementations
Strong background in building and orchestrating data pipelines using services like Azure Data Factory and Databricks
Demonstrated ability to organize and manage data in a lakehouse following medallion architecture;
Background with Databricks Unity Catalog for governance is a plus
Proficient in using Python and SQL for data engineering and analytics development
Familiar with CI/CD practices and tools for automating deployment of data solutions and managing code lifecycle
Comfortable conducting and participating in peer code reviews in Git Hub to ensure quality, consistency, and best practices
Experience in assessing client information technology needs and objectives
Experience in problem‑solving to resolve complex, multi‑component failures
Experience in preparing knowledge transfer documentation and conducting knowledge transfer
Experience working on an Agile team
Desirable Skills   Written and oral communication skills to participate in team meetings, write/edit systems documentation, prepare and present written reports on findings/alternate solutions, develop guidelines / best practices
Interpersonal skills to explain and discuss advantages and disadvantages of various approaches
Technology Stack   Azure Storage, Azure Data Lake, Azure Databricks Lakehouse, Azure Synapse, Azure Databricks
Python, SQL
PowerBI
Git Hub

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