Data Engineer

Unisystech Consulting Inc.; Toronto; Hybrid; CAD 100,000 - 150,000; Full time

Job summary

Unisystech Consulting Inc. is seeking a Data Engineer to design, build, and automate scalable data pipelines for a major banking client. Strong Python and SQL expertise are required to extract, transform, and load data across systems and to ensure data quality for analytics across the organization.

The role is a long-term consulting position with a hybrid work model (2 days onsite in Toronto). The candidate will work with AWS to build pipelines and maintain batch jobs, collaborating with

Qualifications

• 7+ years of experience as a Data Engineer or in a closely related data role.
• Strong proficiency in Python for data manipulation and automation scripts.
• Advanced SQL skills for data transformation, querying, and relational database management.
• Hands-on experience building and maintaining data pipelines within the AWS cloud ecosystem.
• Solid track record building automated ETL pipelines and managing batch workflows.

Responsibilities

• Design, build, and maintain automated data pipelines for enterprise applications.
• Develop efficient ETL processes to extract, transform, and load data across systems.
• Write complex SQL queries and Python scripts for data processing and validation.
• Perform data analysis to troubleshoot pipeline issues, verify data integrity, and optimize performance.
• Collaborate with analytics and business teams to deliver reliable datasets for business reporting.

Skills

Python

SQL

ETL

Data pipelines

Data quality

AWS

Tools

AWS

Job description

We are looking for a Data Engineer to design, build, and automate scalable data pipelines. In this role, you will leverage strong Python and SQL expertise to extract, transform, and load data from varied sources, ensuring high data quality and supporting analytics across the organization. This is a long-term consulting job and the client is one of the major banks.

Working Model: Hybrid – 2 days onsite in Toronto

Location: M1W, Scarborough

In-person Interview is required

Key Responsibilities

• Design, build, and maintain automated data pipelines for enterprise applications.
• Develop efficient ETL processes to extract, transform, and load data across systems.
• Write complex SQL queries and Python scripts for data processing and validation.
• Perform data analysis to troubleshoot pipeline issues, verify data integrity, and optimize performance.
• Collaborate with analytics and business teams to deliver reliable datasets for business reporting.

Requirements & Qualifications

• 7+ years of experience as a Data Engineer or in a closely related data role.
• Strong proficiency in Python for data manipulation and automation scripts.
• Advanced SQL skills for data transformation, querying, and relational database management.
• Hands-on experience building and maintaining data pipelines within the AWS cloud ecosystem.
• Solid track record building automated ETL pipelines and managing batch workflows.
• Strong analytical and problem-solving skills to ensure high data quality and accuracy.