We are looking for a

Data Engineer

to design, build, and automate scalable data pipelines. In this role, you will leverage robust 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.

📌 Data Engineer (Toronto)
🏢 Unisystech Consulting
📍 Toronto