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Added 8 days ago
AC
SAS/Python Developer
Adastra Corporation
Markham, ON
- Full-time
Join Adastra’s Data Engineering team as a SAS/Python Developer, where you will help build and modernize the data platforms that power customer analytics, personalization, marketing, risk,…
Added 8 days ago
N
Software Developer
Nasdaq
Toronto, ON
- Full-time
As a Software Developer reporting to the AVP - Software Development, you'll be part of a growing team in Toronto supporting US exchange operations and our Ocean trading systems beyond…
Added 8 days ago
IC
Data Analytics Engineer
Infotek Consulting Inc.
Toronto, ON
- Contract
Build SQL and Python/PySpark transformations to produce consistent, validated, business-ready datasets.
Added 8 days ago
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Senior Data Engineer
BMO
Toronto, ON · FCP
- Full-time
Build and optimize scalable batch and near-real-time data pipelines using Python, SQL, SAS, AWS Glue, Athena, PySpark, APIs, databases, file-based integrations, and cloud object storage.
Added 8 days ago
B
Data Engineer
BMO
Toronto, ON · FCP
- Full-time
Develop data solutions using Python, SQL, SAS, AWS Glue, Athena, PySpark/Spark, APIs, and cloud-based data services, applying established engineering patterns and standards.
Added 8 days ago
B
Senior Data Engineer
BMO
Toronto, ON · FCP
- Full-time
Build and modernize data-driven workflows using Python, SQL, SAS, AWS Glue, Athena, PySpark/Spark, APIs, and approved automation technologies.
Added 8 days ago
RC
Guidewire Test Lead – P&C Insurance Domain
Realtek Consulting LLC
Markham, ON
- Contract
Experience with Postman, Swagger, SoapUI, REST/SOAP APIs, JSON, XML, and SQL.
Added 8 days ago
FT
Director, Forward Deployed Engineering
FDE Times
Chalk River, ON
- Full-time
Strong hands-on technical skills - proficient in Python and SQL, comfortable going deep on customer architectures and data infrastructure
Added 8 days ago
FT
Forward Deployed Strategist
FDE Times
Chalk River, ON
- Full-time
Strong Python and SQL. You build prototypes and reference implementations, and you can read a customer's codebase and hold a conversation about it
Added 8 days ago
S&
Data Engineer
Silk & Snow
Toronto, ON
- Full-time
We are seeking a versatile and highly motivated Data Engineer to join our data analytics and reporting team. This role is critical in bridging the gap between raw data and actionable…
Added 8 days ago
PI
Senior Data Engineer
PENN Interactive
Canada
- Full-time
As a Senior Data Engineer, you’ll work hand-in-hand with the Data Services team to build, validate and deliver transformed data to meet stakeholder requirements. The ideal candidate has…
Added 8 days ago
RC
Power BI Developer
RAPS Consulting Inc
Mississauga, ON
- $55 to $65 CAD / hour
- Contract
We are seeking an experienced Power BI Developer with a strong background in business intelligence, data warehousing, advanced SQL, and analytics. The ideal candidate will have hands-on…
Added 8 days ago
NB
Senior Data Scientist Implementation and Codification
National Bank of Canada
Richmond Hill, ON
- Full-time
Hands-on experience with SAS, Python, MS Excel (VBA) or SQL.
Added 9 days ago
MF
Senior Manager Client Reporting
Mackenzie Financial Corporation
Toronto, ON
- Other
Advanced proficiency in Excel and Microsoft Office applications; knowledge of SQL, VBA, Python or data analytics tools is an asset.
Added 9 days ago
OR
Network Engineer
OSL Retail Services Inc
Mississauga, ON
- Other
Databases: Working knowledge of database platforms such as Microsoft SQL Server and PostgreSQL, particularly as they relate to infrastructure, performance, and availability considerations.
Added 9 days ago
Production Support Engineer
Capgemini
Toronto, ON
Scripting experience with Shell Scripting, Python, and PowerShell.
Added 9 days ago
L
Senior AI/ML Engineer
Limbic
Remote, Canada
- Full-time
- Remote
Expert-level proficiency in Python and TypeScript/JavaScript.
Added 9 days ago
AG
Research Analyst
Adelphi Group
Toronto, ON
- Full-time
Experience with Advanced Analytical Tools: Experience with analytical tools such as DisplayR, SPSS, Q, R, Python, or SQL is a plus.
Added 9 days ago
T
Information Security Specialist (Vulnerability Management Data Insights & Reporting )
TD
Toronto, ON
- Full-time
· Extract and transform large data sets using approved methods such as REST APIs, scheduled exports, SQL or query tools, Python, PowerShell, or equivalent technologies when analysis cannot…
Added 9 days ago
CO
Application & Integration Technical Analyst
City of Saint John
Saint John, NB
- Full-time
Database querying and transformation: dbt, SQL (writing queries, joins, stored procedures)
Added 9 days ago
TI
Software Engineer (Data)
Themis Intelligence
Toronto, ON · Greater Toronto Area, Canada
- Full-time
Write clean, maintainable Python, TypeScript, and SQL to build data processing components, integrations, and services.
Added 9 days ago
Technical Business Analyst
Scotiabank
Toronto, ON
Hands-on experience with SQL, relational databases, and data analysis, including data validation, reconciliation, and troubleshooting.
Added 9 days ago
A
Python Developer- Gen AI
Ampstek
Montreal, QC
- Contract
Experienced Python Developer with 8+ years of expertise in building and deploying scalable enterprise applications using Python, Generative AI, Large Language Models (LLMs), LangChain, REST…
Added 9 days ago
QW
AI Developer with Python
Quantum World Technologies Inc.
Toronto, ON
- Contract
8+ years of experience in software engineering, including strong proficiency in Python and exposure to AI/ML or Generative AI solutions.
Added 9 days ago
C
Data Engineer
CDAI
Toronto, ON
- Full-time
Design, build, and maintain scalable ETL/ELT data pipelines using Python, SQL, Airflow, Spark that hosted in AWS environment.

BMO

Senior Data Engineer

Toronto, ON, Canada
FCP, Canada

$80,000.00 - $175,000.00 · Full-time

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Job details

Pay: $80,000.00 - $175,000.00
Job type: Full-time
Apply by: Nov 7, 2026
Experience: 7+ years of experience in data engineering, analytics engineering, or a related discipline, with demonstrated ownership of production-grade data and automation solutions.
Posting language: English
Posted: Oct 20, 2026

Original job description

Application Deadline:

11/06/2026

Address:

100 King Street West

Job Family Group:

Data Analytics & Reporting

Design and deliver scalable data, analytics, and automation solutions that transform complex business processes and enable new capabilities across the organization. This role combines hands-on engineering with strong analytical and business acumen to translate complex requirements into governed data models, pipelines, APIs, and intelligent automation solutions.

Key Engineering & Automation Responsibilities

Own end-to-end delivery of data and automation solutions, including pipelines, curated datasets, semantic models, APIs, and analytical data products.
Translate complex business needs into scalable technical solutions, defining requirements, business rules, source-to-target mappings, controls, and acceptance criteria.
Identify and engineer automation opportunities, applying conventional and AI-enabled approaches where appropriate while balancing business value, risk, controls, maintainability, and delivery effort.
Design scalable data models for complex business and investment domains, enabling consistent definitions across reporting, analytics, digital experiences, and downstream applications.
Build and modernize data-driven workflows using Python, SQL, SAS, AWS Glue, Athena, PySpark/Spark, APIs, and approved automation technologies.
Engineer trust and control into data solutions through reconciliation, validation, exception management, human oversight, lineage, auditability, and data-quality controls.
Operationalize production solutions through monitoring, documentation, support processes, failure handling, and sustainable remediation.
Provide technical guidance and mentorship through solution design, code reviews, testing strategies, domain knowledge sharing, and production-readiness reviews.
Communicate data lineage, solution behaviour, assumptions, dependencies, and technical trade-offs effectively across technical, business, and senior stakeholder audiences.

Investment Data & Asset Management

Apply working knowledge of investment products and structures, including mutual funds, ETFs, pooled funds, segregated mandates, separately managed accounts, alternatives, fixed income, equities, derivatives, and cash instruments.
Work across key investment and business data domains, including AUM/AUA, flows, revenue, holdings, transactions, performance, benchmarks, client and account hierarchies, distribution, and product/reference data.
Design solutions around security and reference data, including identifiers, classifications, pricing, FX rates, corporate actions, and effective-dated relationships.
Partner across business and technology teams to translate complex domain requirements into scalable, governed, and maintainable solutions.
Build traceability and reproducibility into data products, supporting analytical, management, client, operational, and regulatory use cases.

Required qualifications

Bachelor’s degree in computer science, engineering, data, or a related discipline, or equivalent practical experience; investment-industry education or credentials are an asset.
7+ years of experience in data engineering, analytics engineering, or a related discipline, with demonstrated ownership of production-grade data and automation solutions.
Advanced proficiency in Python and SQL, with strong engineering practices across modular development, performance optimization, automated testing, troubleshooting, and maintainable code design.
Strong experience with modern data engineering patterns, including ETL/ELT, APIs and data integration, orchestration, relational and dimensional modelling, data warehousing, lakehouse architectures, and distributed data processing.
Proven ability to translate complex investment and operational requirements into scalable data models, controls, workflows, and technical designs.
Experience integrating data across databases, APIs, files, vendor feeds, and enterprise applications.
Strong experience with data profiling, mapping, reconciliation, lineage, metadata, and data-quality management.
Hands-on experience designing and delivering solutions on cloud-based data platforms, preferably AWS, together with modern engineering practices including Git, testing, CI/CD, observability, and monitoring.
Strong communication, facilitation, analytical, and problem-solving capabilities, with the ability to navigate ambiguity and collaborate effectively across technical and business teams.

Preferred qualifications

Experience supporting investment performance, product analytics, distribution analytics, operations, or financial and management reporting.

Familiarity with market and reference-data providers, portfolio/accounting platforms, CRM platforms, transfer-agency systems, fund administration, or comparable investment-data ecosystems.

Experience with modern data platforms and technologies such as AWS data services, Databricks, Snowflake, Redshift, SageMaker, Airflow, and dbt, or comparable technologies.

Experience modernizing legacy data and reporting ecosystems, including SAS, TIBCO IBI WebFOCUS, spreadsheet-driven processes, and other legacy or on-premises platforms.

Familiarity with enterprise data governance and control frameworks, including privacy, security, entitlements, data lineage, records management, and regulatory controls within financial services.

Exposure to AI-enabled automation and advanced analytics patterns, including the controlled integration of AI capabilities into production workflows.

What Success Looks Like

Less reliance on manual and spreadsheet-dependent processes through scalable, controlled, and supportable automation.
Consistent business definitions and reusable investment-data models across analytical and operational data products.
Faster translation of business needs into production solutions, connecting investment-domain requirements with technically sound designs.
Fewer reporting breaks, manual interventions, and downstream data issues through stronger controls, reconciliation, exception handling, and observability.
Greater stakeholder confidence in critical investment data, including AUM, flows, revenue, performance, product, client, and operational information.
Practical adoption of automation and AI capabilities where they deliver measurable value while maintaining appropriate controls, traceability, and human oversight.
Stronger collaboration between business and operations teams, with complex investment concepts translated into maintainable data models, workflows, and engineering solutions.

Salary:

$80,000.00 - $175,000.00

Pay Type:

Salaried

The above represents BMO Financial Group’s pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position.

BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset.

To find out more visit us at https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

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More about this job

Responsibilities

Design and deliver scalable data, analytics, and automation solutions to transform complex business processes. Own the end-to-end delivery of data pipelines, curated datasets, and intelligent automation while ensuring data quality and governance.

Requirements

Requires a bachelor's degree in computer science, engineering, or a related field and 7+ years of experience in data engineering. Candidates must possess advanced proficiency in Python and SQL, along with strong experience in cloud-based data platforms and modern engineering practices.

Skills

Python
SQL
Data engineering
AWS
Data modeling
ETL/ELT
APIs
PySpark
Data quality management
Automation
Cloud platforms
CI/CD
Data lineage
Investment domain knowledge
Analytical skills
Mentorship

Benefits

Health insurance
Tuition reimbursement
Accident insurance
Life insurance
Retirement savings plans

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Python
SQL
AWS Glue
Athena
PySpark
ETL
ELT
Data Modeling
Data Warehousing
Lakehouse Architecture
APIs
Automation
Git
CI/CD
Observability
Databricks
Snowflake
Redshift
SageMaker
Airflow
dbt
SAS
Investment Data
Data Governance
Data Lineage
Financial Services
Metadata Management
Performance Optimization
Distributed Data Processing

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