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Added 1 day ago
IF
Data Solution Architecture Advisor
iA Financial Group
Montreal, QC · Quebec, QC
- Full-time
Demonstrates extensive expertise in data architectures and technologies, including Snowflake, Databricks, Azure SQL, ADF, SQL, Python, APIs, data modelling, as well as data governance and…
Added 1 day ago
RU
Supervisor, Data Architect
RSM US LLP
Toronto, ON
- Full-time
We are seeking a skilled Business Intelligence and Data Engineering professional with a strong background in design and development, data modeling, and business analytics. This individual…
Added 1 day ago
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Software Developer - Cloud Platform
Nakisa
Montreal, QC
- Full-time
As a Software Developer on our Platform Engineering team, you will help design, build, and maintain the cloud-native services and tools that power Nakisa's product portfolio for Fortune…
Added 1 day ago
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Kafka Platform Administrator / Kafka Developer
Manpower
Calgary, AB
- Contract
We are looking for an experienced Kafka Platform Administrator / Kafka Developer with strong expertise in Apache Kafka, Kafka on-premises and cloud environments, and Red Hat OpenShift…
Added 1 day ago
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Data Scientist
VySystems
Mississauga, ON
- Full-time
Strong Python development with FastAPI or Flask.
Added 1 day ago
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Senior Platform Automation Engineer
RBC
Toronto, ON
- Full-time
4+ years of professional software development and platform engineering in financial technology or financial services, with proven expertise in Python, DevOps, and multi-cloud automation.
Added 1 day ago
Bilingual Senior Specialist, Software Engineering (CI/CD & Automation Engineering)
CMHC - SCHL
Ottawa, ON · Montreal, QC
The work you do and the work we do together matters. We come to work every day with a common purpose: to contribute to a well-functioning housing system.
Added 1 day ago
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Java / Python Engineer
Dexian
Mississauga, ON
- $60 to $65 CAD / hour
- Contract
8+ years of professional software engineering experience, with demonstrable experience as a Full-Stack Developer transitioning into an FDE-style, customer-facing delivery role.
Added 1 day ago
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Senior Data Engineer
Exchange Solutions
Toronto, ON · Greater Toronto Area, Canada
- Full-time
Write advanced SQL and Python to develop transformations, frameworks, automation, and reusable engineering tooling.
Added 1 day ago
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Oracle Database Administrator
Apptoza Inc.
Toronto, ON
- Contract
1.Collaborate with application development teams on data modeling| schema design| and deployment of complex PLSQL packages| procedures| triggers| and views.
Added 1 day ago
CE
Senior Geoscience Technologist
Cenovus Energy
Calgary, AB
- Full-time
Basic knowledge of Python, SQL or other programming languages is considered an asset.
Added 1 day ago
CG
AI Product Developer
ConeTec Group
Burnaby, BC
- Full-time
We're hiring an AI Product Developer: an experienced software developer who builds products with AI coding agents and builds AI into those products. You'll work directly with the people who…
Added 1 day ago
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Data Integration Engineer
Prophix
Toronto, ON · Etobicoke, ON
- Full-time
…to integration strategy and architecture while collaborating with technical and business stakeholders to deliver effective solutions. This role requires a strong foundation in data systems,…
Added 1 day ago
NB
Senior Data Scientist
National Bank of Canada
Montreal, QC
- Full-time
Demonstrated programming skills, particularly with SAS, SQL, Python, or other programming and automation languages.
Added 1 day ago
NB
Senior Data Engineer
National Bank of Canada
Montreal, QC
- Full-time
Integrate and automate data between systems and business applications, then optimise processing with SQL and Python.
Added 1 day ago
Solution Architect
PCL Construction
Edmonton, AB
We're a team of builders who care deeply about what we create and who we build with. That includes you. We are not only shaping the future of construction, we are also committed to shaping…
Added 1 day ago
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Actuarial Analyst I - Project Development & Optimization
TD
Toronto, ON
- Full-time
Advanced knowledge in programming languages (e.g., R, Python, SQL, VBA or other)
Added 1 day ago
SH
Senior Financial Analyst
Spectrum Health Care
Toronto, ON
- $85,000 to $100,000 CAD / year
- Full-time
Spectrum Health Care is looking for a CPA-designated Senior FP&A Analyst with strong analytical judgment, advanced Power Query and Power BI skills and a proactive approach to…
Added 1 day ago
BC
Supply Chain Planner
Bimbo Canada
Toronto, ON · Etobicoke, ON
- Full-time
Proficiency with MS Excel; experience with Oracle, WMS, Power BI/Tableau/SQL/Python is an asset.
Added 1 day ago
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Software Engineer - QC(Local)
Yochana
Montreal, QC
- Contract
Experience with relational databases such as PostgreSQL, Oracle, or SQL Server.
Added 1 day ago
AC
Ingénieur·e données
ALTEN Canada
Montreal, QC
- Full-time
Maîtrise de Python 3, PySpark (DataFrame API, Spark SQL), SQL et Git
Added 1 day ago
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Data Analyst
GiveBridge
Toronto, ON
- Full-time
Nice to Have: Experience with Zoho Analytics, Python, APIs/workflow automation, or CRM, fundraising, financial, sales, or transaction data.
Added 1 day ago
HB
Trading Application Support Engineer: $180,000cad + Bonus (Quant Fund)
Hunter Bond
Montreal, QC
- Full-time
…production support for cutting-edge electronic trading systems with hands-on engineering and automation…
Added 1 day ago
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Staff Back End Engineer (Data Platform)
Forma.ai
Toronto, ON
- Full-time
As a Staff Engineer, you are expected to operate with a high degree of ownership and trust. This includes proactively identifying architectural risks, surfacing edge cases or constraints…
Added 1 day ago
7
AI Data Architect
7shifts
Toronto, ON · Saskatoon, SK
- $160,000 to $200,000 CAD / year
- Full-time
A background in data engineering, analytics engineering, software development, or a related systems role (BI and analytics paths count too), with hands-on Python and SQL

Exchange Solutions

Senior Data Engineer

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Dec 3, 2026
Experience: A minimum of 5 years’ progressive data engineering experience, with a demonstrated record of owning production data pipelines end-to-end.
Posting language: English
Posted: Nov 3, 2026

Original job description

Role Summary

The Senior Data Engineer reports to the Director, Information Technology Operations and designs, builds, and scales the data systems that support analytics, AI-enabled experiences, and organizational decision-making. The role owns significant parts of the data platform, including production pipelines, transformation layers, data models, semantic layers, data quality, observability, and engineering standards. It provides technical direction, mentors engineers and analysts, and partners with technical and business teams to deliver trusted, well-modelled data products. The role also evaluates and implements AI-assisted data engineering capabilities to improve pipeline development, transformation, documentation, metadata, data quality, and governed access to enterprise data while maintaining appropriate engineering controls and review.

Primary Responsibilities:

Data Platform Architecture & Technical Direction

Responsible for key contribution of significant parts of the data platform and drive long-term architectural decisions related to tooling, data modelling, semantic architecture, automation, and scalability.
Design data platform capabilities that reliably support analytics, reporting, operational use cases, and AI-enabled experiences.
Evaluate technical options and establish reusable patterns that improve platform maintainability, extensibility, and engineering effectiveness.

Pipeline Development & Transformation

Design, build, and maintain scalable, reliable production data pipelines and transformation layers using dbt and a medallion Bronze, Silver, and Gold architecture.
Write advanced SQL and Python to develop transformations, frameworks, automation, and reusable engineering tooling.
Responsible for production data pipelines end-to-end, including design, development, testing, deployment, monitoring, troubleshooting, optimization, and ongoing support.

Data Modelling & Semantic Architecture

Lead data modelling across dimensional models, slowly changing dimensions, fact and dimension design, and well-structured Silver and Gold layers.
Design and evolve semantic layers that define business entities, metrics, relationships, calculations, and governed business logic for consistent use across BI, analytics, and AI applications.
Develop metadata-driven and governed data structures that make enterprise data discoverable, understandable, and consistently consumable.

AI-Assisted Data Engineering & Enablement

Evaluate and apply AI-assisted engineering approaches to accelerate pipeline design, transformation logic, SQL generation, testing, documentation, troubleshooting, and optimization while maintaining strong review and engineering controls.
Explore AI-assisted schema understanding, metadata generation, relationship discovery, business-concept mapping, and generation of semantic definitions.
Partner with Analytics and Innovation AI Labs to enable natural-language-to-data, intelligent analytics, semantic retrieval, and other AI or LLM-based uses of governed enterprise data.

Data Quality & Observability

Responsible for evolving key elements of the data quality strategy, including testing frameworks, monitoring, alerting, service levels, observability, anomaly detection, and platform-wide validation.
Implement controls that identify pipeline, transformation, model, metadata, and semantic-layer issues early and support timely root-cause analysis and remediation.
Promote trusted data products through clear quality standards, transparent monitoring, and continuous improvement of reliability and usability.

Engineering Practices & Delivery Standards

Establish and champion engineering practices covering version control, CI/CD, code review, documentation, automated testing, clean maintainable code, and dbt project standards.
Develop reusable frameworks and automation that improve delivery consistency, reduce manual effort, and support safe changes across data environments.
Contribute to governance, cataloguing, lineage, metadata management, and data-contract practices that strengthen understanding and control of enterprise data.

Partnership, Mentorship & Team Growth

Collaborate with analysts, data scientists, product teams, and business stakeholders to translate business requirements into trusted, well-modelled data products.
Mentor and support engineers and analysts, provide technical guidance, and contribute to team capability and engineering maturity.
Communicate architecture decisions, data definitions, quality expectations, risks, and technical trade-offs clearly to technical and business stakeholders.
Contribute to the culture of the company, fostering Exchange Solutions' core values and policies.

Capability Requirements - Education, Skills & Experience:

Education & Experience

Post secondary education, with a degree in Data Engineering.
A minimum of 5 years’ progressive data engineering experience, with a demonstrated record of owning production data pipelines end-to-end.
Experience designing, developing, and operating data platforms that support analytics, reporting, operational use cases, or AI-enabled applications.
Experience translating business and analytical requirements into trusted data products in collaboration with technical and business stakeholders.
Experience leading data engineering projects or mentoring engineers and analysts is an asset.
Experience in a loyalty, retail, financial services, or other data-intensive environment is an asset.

Technical Skills

Expert SQL skills and strong Python proficiency for data engineering; working knowledge of Jinja.
Deep hands-on dbt experience, including advanced modelling, macros, packages, testing, documentation, and project architecture using dbt Core or dbt Cloud.
Strong command of medallion architecture and data modelling, including dimensional modelling, slowly changing dimensions, fact and dimension design, and semantic layers.
Experience designing or working with semantic models, governed business metrics, metadata-driven architectures, or governed business definitions.
Experience with cloud data warehouses such as Snowflake, BigQuery, Databricks, or Redshift and with cloud platforms such as AWS, Azure, or GCP.
Experience building and operating data quality, testing, monitoring, alerting, lineage, cataloguing, or observability capabilities.
Solid software engineering practices covering Git, CI/CD, automated testing, code review, documentation, and clean maintainable code.
Experience with orchestration tools such as Airflow, Dagster, Prefect, dbt Cloud, or Snowflake Tasks is an asset.
Familiarity with streaming or real-time data and infrastructure-as-code tools such as Terraform is an asset.
Ability to evaluate and safely incorporate AI-assisted tools into data and software engineering workflows, including development assistance, metadata enrichment, automated documentation, and intelligent data-quality tooling.
Experience with AI or LLM-enabled data platforms, natural-language-to-SQL, semantic retrieval, knowledge graphs, ontologies, semantic views, or agentic data engineering workflows is an asset.

Competencies & Behaviours

Ownership & Accountability - Takes end-to-end responsibility for production data pipelines, platform components, engineering quality, and resolution of risks or failures.
Architecture & Technical Judgement - Makes practical, forward-looking decisions that balance scalability, reliability, maintainability, data quality, delivery needs, and long-term platform direction.
Communication - Translates business requirements and complex data concepts into clear models, technical decisions, documentation, and guidance for technical and non-technical stakeholders.
Collaboration & Mentorship - Builds effective relationships across engineering, analytics, data science, Product, and business teams and raises team capability through practical coaching and knowledge sharing.
Innovation & Responsible AI - Explores new tools and AI-assisted approaches thoughtfully, validates their value, and applies appropriate review, governance, quality, and security controls.
Attention to Detail - Applies a disciplined approach to modelling, transformation logic, testing, metadata, semantic definitions, documentation, and production changes.

Apply About employer

More about this job

Responsibilities

Design, build, and operate scalable data platform components, production pipelines, transformation layers, data models, and semantic layers that support analytics, reporting, and AI-enabled applications. Set engineering standards, improve data quality and observability, evaluate responsible AI-assisted engineering approaches, and provide technical direction and mentorship while partnering with business and technical teams.

Requirements

Requires post-secondary education with a degree in Data Engineering and at least five years of progressive data engineering experience, including end-to-end ownership of production pipelines. Candidates should have expert SQL, strong Python, deep dbt experience, data modeling and cloud data platform expertise, and familiarity with engineering practices, data quality, and responsible AI-assisted tools.

Skills

SQL
Python
dbt
Jinja
Data Pipeline Engineering
Medallion Architecture
Dimensional Modeling
Semantic Layers
Cloud Data Warehousing
Data Quality and Observability
CI/CD
Git
Data Governance
AI-Assisted Engineering
Mentorship

Visa sponsorship

Not detected in the job text

Keywords

SQL
Python
Jinja
dbt Core
dbt Cloud
Medallion Architecture
Bronze-Silver-Gold Architecture
Dimensional Modeling
Slowly Changing Dimensions
Semantic Layers
Snowflake
BigQuery
Databricks
Redshift
AWS
Azure
GCP
Airflow
Dagster
Prefect
Snowflake Tasks
Terraform
CI/CD
Git
Data Quality
Data Observability
Data Governance
Metadata Management
Natural-Language-to-SQL
LLMs

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