Business System Analyst/Data Anlyst

Keasis; Toronto; Hybrid; CAD 83,000 - 124,000; Part time

Job summary

A tech-driven firm in Toronto is seeking a Business System Analyst for a contract role. The successful candidate will be responsible for understanding the auto ingestion process and building a strategic platform on Azure from legacy systems. Key duties include improving data mapping, analyzing current data processes for enhancements, and ensuring data accuracy. Experience with SQL Server, PySpark, and Azure Databricks is essential. This hybrid position offers a collaborative work environment.

Qualifications

• Minimum exposure to data integration projects and data validation.
• Experience in data ingestion, transformation, and validation.
• Ability to collaborate with cloud platforms (Azure Databricks) and legacy systems.

Responsibilities

• Understand the auto ingestion process and its validation.
• Build a strategic platform on Azure from legacy systems.
• Improve data mapping efficiency and correct data in source.
• Analyze current data processes for future improvements.
• Streamline data for simultaneous use across platforms.
• Ensure data accuracy checks on datasets for cloud platforms.
• Work with SQL server and PySpark on relevant tasks.
• Collaborate using Confluence.
• Utilize Azure Databricks for data-related tasks.

Skills

Auto ingestion process understanding

Data mapping efficiency

Data analysis for improvement

SQL Server experience

PySpark experience

Working with Azure Databricks

Experience in Confluence

Tools

Azure

SQL Server

PySpark

Azure Databricks

Confluence

Job description

Role: Business System Analyst

Location: Toronto, ON (Hybrid)

Type: Contract

Responsibilities

• Understanding the process of auto ingestion and its validation
• Building a strategic platform on Azure from the legacy systems
• Experience in Data mapping and doing it in a more efficient way and if anything has been done wrong in the source system then get corrected
• Analyse the data what is being done today and how it can be further improved for future
• Streamline the data so that it can be used simultaneously at multiple places
• Make sure data completion and data accuracy checks have been done on datasets bringing out to cloud platforms
• Experience in SQL server and PySpark as legacy system has SQL and strategic platform has PySpark
• Experience working in confluence
• Experience working on Azure Databricks