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939

Asset Management jobs in Canada

Data Engineer

SESAMm SAS

Toronto
On-site
CAD 80,000 - 110,000
30+ days ago
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Vice President, Value Office, Finance

EQ Bank | Equitable Bank

Toronto
On-site
CAD 200,000 - 250,000
30+ days ago

Data Scientist

SESAMm SAS

Toronto
On-site
CAD 80,000 - 110,000
30+ days ago

Senior Data Modelling & Detection Analytics Consultant

Capco

Toronto
On-site
CAD 125,000 - 150,000
30+ days ago

Financial Planning Consultant - Whitby, ON

Canadian Imperial Bank of Commerce

Toronto
Hybrid
CAD 80,000 - 100,000
30+ days ago
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Senior Asset Management Data & Interface Lead (Hybrid)

Deloitte Canada

Toronto
Hybrid
CAD 80,000 - 138,000
30+ days ago

Hybrid District Sales Associate | Finance Growth

Mackenzie Investments

Montreal
On-site
CAD 50,000 - 70,000
30+ days ago

Senior Project Manager: Financial Services Transformation

Capco

Toronto
On-site
CAD 90,000 - 120,000
30+ days ago
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Senior Natural Gas Trader

NRG Energy

Calgary
On-site
CAD 80,000 - 100,000
30+ days ago

Project Manager, Contact Centre

Capco

Toronto
On-site
CAD 80,000 - 100,000
30+ days ago

Investment Marketing Manager for Advisors - Hybrid/Remote

Fidelity Canada

Toronto
Hybrid
CAD 90,000 - 120,000
30+ days ago

Quality Assurance Analyst II

HireTalent

Montreal
On-site
CAD 70,000 - 90,000
30+ days ago

Manager of Administration (1.0 FTE)

Giishkaandago'Ikwe Health Services

Fort Frances
On-site
CAD 70,000 - 90,000
30+ days ago

IT Administration Manager

Targeted Talent

Montreal
Hybrid
CAD 80,000 - 100,000
30+ days ago

Infrastructure Manager

Targeted Talent

Montreal
Hybrid
CAD 90,000 - 120,000
30+ days ago

IT Manager

Targeted Talent

Montreal
Hybrid
CAD 60,000 - 80,000
30+ days ago

Back of House - Dishwasher

Moxies

Red Deer
On-site
< CAD 30,000
30+ days ago

Talent Acquisition Manager

Brookfield Asset Management

Toronto
On-site
CAD 80,000 - 100,000
30+ days ago

Field Operations Summer Student - NEBC

ARC Resources Ltd.

Dawson Creek
On-site
CAD 30,000 - 60,000
30+ days ago

Senior Quality Support Team Specialist (Permanent)

Babcock International

Victoria
On-site
CAD 80,000 - 99,000
30+ days ago

Director of Enterprise Integrations & Delivery

MaintainX

Montreal
On-site
CAD 100,000 - 150,000
30+ days ago

Solution Architect (Data)

Maafor

Hamilton
On-site
CAD 90,000 - 140,000
30+ days ago

Assistant Manager- Marketplace

Hard Rock Hotels

Ottawa
On-site
CAD 50,000 - 70,000
30+ days ago

Remote IT Hardware & Logistics Analyst - Data-Driven

Samsara

Canada
Hybrid
CAD 80,000 - 88,000
30+ days ago

Bilingual IT Systems Support & Asset Mgmt (Onsite)

Motion Recruitment Partners LLC

Saint-Laurent-de-l'Île-d'Orléans
On-site
CAD 45,000 - 60,000
30+ days ago

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Data Engineer
SESAMm SAS
Toronto
On-site
CAD 80,000 - 110,000
Full time
30+ days ago

Job summary

A leading data analytics firm in Toronto is seeking a Data Engineer to join an innovative AI platform project. The role involves designing data architectures, developing pipelines for investment analysis, and collaborating with teams across finance. The ideal candidate has a Master's degree and 3–5 years of experience with data engineering. Benefits include remote work flexibility, professional development opportunities, and a multicultural work environment.

Benefits

Remote work flexibility
Career development opportunities
Professional training and mentorship
Multicultural work environment
Global collaboration opportunities

Qualifications

  • 3–5 years of hands-on experience designing and maintaining large-scale data pipelines.
  • Proven experience working with structured and unstructured financial data or other complex data domains.
  • Experience in finance, consulting, or private equity environments.

Responsibilities

  • Design and maintain robust data pipelines and architectures.
  • Develop scalable data infrastructure and monitor data flow performance.
  • Collaborate with data scientists and investment teams to operationalize analytics.
  • Automate data workflows and implement CI/CD pipelines.

Skills

Python
SQL
Cloud platforms (AWS, Azure, GCP)
Data orchestration tools (Airflow, Prefect)
Data modeling
API integration
Big data frameworks (Spark, Kafka)
Version control (Git)
DevOps practices (CI/CD)
Communication skills

Education

Master’s degree in Data Engineering or Computer Science
Job description

SESAMm (www.sesamm.com) extracts behavioral insights from millions of unstructured text data sources across the public internet in over 100 languages, helping clients distill valuable intelligence on businesses and their customers to make investment decisions and manage risk.

We work with many well‑known firms around the world in private equity, investment banking, insurance, and asset management to apply Natural Language Processing and Artificial Intelligence algorithms to track e‑reputation, competitive positioning, sentiment analysis, risk and ESG factors.

SESAMm is growing quickly, with over 90 team members around the globe and offices in Paris, New York, London, Metz, Tunis, and Tokyo.

Key technologies: Alternative Data, Natural Language Processing, Machine Learning and Quantitative Analysis.

Are you looking for a new challenge? Do you dream of joining a growing company, proposing new ideas, and taking part in innovative processes?

At SESAMm, everyone brings their ideas, skills, and creativity. We value collaboration, support and teamwork. We learn every day from the experience of this great team and we constantly take up new challenges. We are proud of the work accomplished and to participate in the success of this great adventure!

The Data Engineer Role

SESAMm, in partnership with one of the largest private equity (PE) firms in the United States, is seeking a data engineer to join an exciting AI platform project designed to transform investment analysis. This project is at the cutting edge of private equity, leveraging advanced artificial intelligence (AI) to improve data‑driven decision‑making. As a data engineer, you will contribute to a groundbreaking platform used by deal teams to accelerate and enhance due diligence.

Key Responsibilities
  • Data Architecture & Pipeline Development: Design, build, and maintain robust data pipelines and architectures to support private equity investment workflows. Ensure seamless ingestion, transformation, and integration of large, diverse datasets (financial, ESG, market, and alternative data) from multiple internal and external sources.
  • Scalability, Performance & Reliability: Develop scalable data infrastructure, monitor and optimize data flow performance, reliability, and data quality. Ensure compliance with security, privacy, and governance standards.
  • Collaboration with Data Science & Investment Teams: Partner with data scientists, investment professionals, and operations teams to operationalize analytics. Enable efficient data access, versioning, and reproducibility across the AI and analytics platform.
  • Automation & Continuous Improvement: Automate data workflows, implement CI/CD pipelines, and contribute to the continuous improvement of data engineering practices. Evaluate new tools and architectures to enhance efficiency, scalability, and cost‑effectiveness.
Desired Background and Skills
Education
  • Master’s degree in Data Engineering, Computer Science, or a related technical field.
Experience
  • 3–5 years of hands‑on experience designing and maintaining large‑scale data pipelines.
  • Proven experience working with structured and unstructured financial data or other complex data domains.
  • Experience collaborating in finance, consulting, or private equity environments is a must.
Skills
  • Advanced proficiency in Python and SQL for data processing and transformation.
  • Hands‑on experience with cloud data platforms (e.g. AWS, Azure, GCP, or Databricks) and data workflow orchestration tools (e.g. Airflow, Prefect, or Dagster).
  • Strong understanding of data modeling, schema design, and API integration.
  • Experience with big data frameworks (Spark, Kafka, Delta Lake, etc.) is highly desirable.
  • Familiarity with version control (Git) and DevOps practices (CI/CD pipelines).
  • Strong communication skills and ability to work cross‑functionally with non‑technical stakeholders. Fluency in English; French is a plus.
Benefits of Working at SESAMm

Flexibility: Team members can work remotely and have the opportunity to work with colleagues around the world.

Work Environment: SESAMm is multicultural, with technology, sales, and management teams in the US, France, and Tunisia making important contributions to the company’s growth.

Career Development: SESAMm is growing rapidly, creating ongoing opportunities for personal and professional growth. This dynamic environment allows you to shape the company’s culture and evolution.

Professional Development: Work alongside industry‑leading experts and gain valuable exposure to advanced AI and ML technologies applied in private equity. This role offers a unique opportunity to deepen your expertise in these cutting‑edge applications.

Mentorship & Training: SESAMm provides structured training and mentorship, with a strong emphasis on knowledge‑sharing. Internally and externally led training sessions are organized, and we offer access to educational platforms, encouraging you to expand your AI skill set.

Global Perspective: Collaborate with teams based across Europe and the United States, gaining hands‑on international experience in a fast‑paced, high‑impact environment. This global perspective helps broaden your skill set and provides insights into international market dynamics.

Transparency: You will be kept apprised of the company’s continuing evolution and performance through monthly "Ask Me Anything" meetings, frequent business/finance updates, and strategy‑sharing discussions.

Well‑being: Building a good culture is key to building a good business at SESAMm. We focus on being a learning organization that values and supports teamwork, thoughtfulness, and work/life balance.

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* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.

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