Data Engineer

Position: Data Engineer I
## Data Engineer IApplyremote type:
On Site locations:
Toronto, Ontario time type:
Full time posted on:
Posted Todaytime left to apply:
End Date:
August 8, 2026 (21 days left to apply) job requisition :
R 1498701
*
* Work Location:

** Toronto, Ontario, Canada
*
* Hours:

** 37.5
** Line of Business:
** Technology Solutions
** Pay Details:**$69,700 - $98,400 CADTD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience  compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.
*
* Job Description:

**** Purpose
* * We are the Data Strategy & Implementation team. We own the pipelines that  bring data into our platform and the curated data products that flow back out  to our partners. From onboarding a brand-new source, to building and hardening  the ETL that moves and shapes it, to publishing governed data products, we are  the team that turns raw, scattered data into trusted, reusable assets the wider  business depends on.
** People
* * You will join a close-knit group of data engineers and analysts who take real  ownership of what they build. We value people who dig into problems end to end,  recognize each other's contributions, and are always looking for a smarter,  faster way to work — including making the most of modern AI tooling.
** Presence
* * We work in a hybrid model, combining focused remote days with regular in-person  collaboration. You will partner daily with source-system owners, platform and  networking teams, and the partners who consume our data products.

** WHY THIS ROLE MATTERS
** Everything downstream — analytics, reporting, AI models, regulatory and  compliance deliverables — depends on data arriving cleanly, securely, and on  time. As a Data Engineer on this team, you are at the front of that chain. You  will onboard new sources into our ingestion framework, build and debug the  Databricks notebooks and ETL that process them, and open the right paths through  firewalls and access controls so the data can flow.

Your work directly  determines how quickly the business can act on new data and how much they can  trust it.

** WHAT YOU'LL DO
*** Independently design, build, and debug Databricks notebooks and ETL
* pipelines that ingest and transform data from a wide range of sources.
* Onboard new data sources into our ingestion framework end to end — from first
* connection through to a production-ready, monitored pipeline.
* Establish secure connectivity to source systems: work through networking
* fundamentals to open firewalls, and provision the right access across diverse
* database and API technologies.
* Write secure, high-performance ETL code that scales, using Python, Spark, and
* PySpark on Azure Data Factory, Azure Databricks, ADLS, and Delta Lake.
* Own the reliability of your pipelines — troubleshoot issues, tune performance,
* and keep data flowing accurately into curated data products.
* Collaborate with source owners, platform, networking, and partner teams to
* deliver ingestion and data-product work on the release cadence.
** WHERE YOU'LL WORK
** This is a hybrid role. You will spend part of your week working remotely and  part collaborating with the team and stakeholders in person. Expect close  day-to-day partnership with the data engineers, analysts, and platform teams who  keep our ingestion and data-product delivery moving.

** EXPERIENCE AND / OR EDUCATION
*** Hands-on experience building and debugging data pipelines on Azure Databricks,
* Azure Data Factory, ADLS, and Delta Lake.
* Strong programming skills in Python, plus practical experience with Spark and
* PySpark for large-scale data processing.
* Solid grounding in…