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Added 1 hour ago
Winter 2027: Operations Analyst Co-op (12 months)
CGI
Toronto, ON
Full-time
…growing. We are looking for a highly motivated Sales Operations Analyst Co-op student to join our growing Business Operations team supporting the Toronto Financial Services (TFS) business…
Added 1 hour ago
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Full-time
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Full-time
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Added 6 hours ago
RPA Business Systems Analyst (BSA)
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Contract
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Added 6 hours ago
Sr. Data Analyst -1806 (Asset Management)
Amyantek
Toronto, ON
Contract
 Candidates should have 5+ years of senior-level Data Engineering experience.
Added 6 hours ago
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RPA Business Systems Analyst
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Added 9 hours ago
Solution Product Marketing Manager - Canada
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Privacy Analyst (Temporary: October 2026 - October 2028)
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Added 12 hours ago
Privacy Analyst
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Amyantek

Sr. Data Analyst -1806 (Asset Management)

Toronto, ON, Canada

Job type: Contract
Apply by: Oct 30, 2026
Posting language: English
Posted: Sep 30, 2026

Apply About employer

Applications open in a new tab.

Original job description

Position title: 1806 - Senior Data Engineer

1 year contract with Sunlife with a possibility of extension,

Working Status: Hybrid – Onsite Tuesday, Wednesday, Thursday

Location: 1 York Street, Toronto, Ontario M5J 0B6

Manager Notes

 Industry experience is the highest priority. Candidates must have direct experience working

within Asset Management. Experience with Pension Funds, Wealth Management, or Capital

Markets is also acceptable, with Asset Management being the strongest preference.

 Candidates should have 5+ years of senior-level Data Engineering experience.

 The manager is looking for candidates whose previous responsibilities closely align with the

work they will be performing in this role. Experience should be directly relevant, not just

exposure to similar technologies.

 Snowflake is the preferred data platform, as it is the organization's primary technology.

However, strong senior candidates with experience leading large enterprise data initiatives

using other modern cloud data platforms may still be considered.

 Experience with Databricks, Azure, AWS, or similar cloud data technologies is highly

desirable.

 Exposure to AI or AI-enabled data solutions is considered a strong asset.

 Candidates should have experience delivering large-scale enterprise data engineering

projects and working within mature data organizations.

 The hiring manager values industry knowledge over specific technologies. A candidate with

strong Asset Management data experience can more easily learn a new technology stack

than a technically strong candidate with no investment industry background.

 Candidates should have experience supporting data platforms involving investment,

portfolio, securities, holdings, market, or performance data.

Critical Experience:

 7–8 years of experience in asset management is mandatory. Candidates must have hands-

on experience working in the asset management domain and be highly proficient with

Snowflake.

Must have Requirements:

7+ years of experience working in data‑driven organizations on large‑scale, end‑to‑end data

initiatives.

5+ years of hands‑on experience building data platforms, applications, and pipelines using

cloud‑native technologies (AWS, Azure, GCP).

Deep understanding of cloud data ecosystems (Snowflake - including Warehouses, query

optimization, and cost governance, Oracle, Hadoop, etc.). Experience with data ingestion

and flow management tools.

Strong programming skills in Python, Java, Scala, and SQL.

Expertise with AWS services including S3, EC2, EKS, Glue, SageMaker, Athena, and

Redshift.

Experience designing APIs and microservices.

Required Soft Skills:

 Strong communication, negotiation, and stakeholder‑management skills.

 Proven ability to influence, lead change, and drive measurable outcomes.

Nice to have Requirements:

 Experience with data visualization tools (Power BI, Tableau) is an asset.

Education:

 Bachelors/ master’s degree in computer science or a related technical field.

Top Performer:

A curious builder who thrives across the end‑to‑end data lifecycle - from analytics to

engineering. Someone who understands modern data stacks, embraces AI‑driven innovation,

and enjoys creating scalable, high‑impact data solutions.

Role Summary

As a Senior Data Engineer, you will be a key contributor to SLC’s enterprise data platform

strategy, enabling self‑serve analytics, scalable data products, and robust data governance

across Pan‑SLC portfolios. You will work within the data platform squad to build foundational

data capabilities using Snowflake and other cloud‑native technologies.

In this senior, high‑impact role, you will architect, design, and implement secure, scalable, and

high‑performance data solutions that power business‑critical use cases. You will mentor junior

engineers, influence architectural decisions, and drive the evolution of our engineering practices

to ensure the platform remains innovative, reliable, and future‑ready.

Key Accountabilities

Engineering & Architecture

 Design and implement end‑to‑end solutions for data, cloud, and software engineering

needs.

 Collaborate with technical leads to align engineering decisions with the strategic vision of

Pan‑SLC.

 Build scalable data pipelines, data lakes, and data warehouse solutions.

Data Marketplace & Integrations

 Evaluate and implement system integrations supporting SLC’s vision for data‑as‑a‑product

and enterprise data discovery.

Platform Engineering

 Partner with DBTS and enterprise engineering teams to identify, evaluate, and deploy tools

and technologies required for current and future platform needs.

 Champion inner‑sourcing practices within Sun Life teams to enable collaborative

development.

DevOps & Governance

 Establish and enhance DevOps practices to improve developer experience and

time‑to‑market.

 Advocate for and implement strong data governance, quality, and reliability practices.

Cross‑Functional Collaboration

 Work with analysts, business stakeholders, and product teams to gather requirements and

translate them into technical solutions.

 Support business‑critical use cases by delivering secure, scalable, and high‑performance

data products.

 Proactively monitor workflows, resolve bottlenecks, and troubleshoot data issues.

Apply About employer

More about this job

Responsibilities

Design, build, and maintain secure, scalable data platforms, pipelines, lakes, warehouses, integrations, and data products using Snowflake and cloud-native technologies. Collaborate with business and technical teams, mentor junior engineers, improve DevOps and governance practices, and monitor and troubleshoot data workflows.

Requirements

Requires 7–8 years of hands-on asset management experience, 7+ years delivering large-scale data initiatives, and 5+ years building cloud-native data platforms and pipelines; strong Snowflake expertise is essential. Candidates should have strong programming skills in Python, Java, Scala, and SQL, experience with AWS services and API or microservices design, and excellent communication and stakeholder-management skills; a bachelor's or master's degree in computer science or a related technical field is specified.

Skills

Asset Management
Snowflake
Data Engineering
Cloud Data Platforms
Data Pipelines
Python
Java
Scala
SQL
AWS
Azure
GCP
Data Governance
API Design
Microservices
Stakeholder Management

Visa sponsorship

Not detected in the job text

Keywords

Asset Management
Snowflake
Data Engineering
Enterprise Data Platforms
Cloud-Native Technologies
AWS
Azure
GCP
Databricks
Python
Java
Scala
SQL
Data Pipelines
Data Lakes
Data Warehousing
Data Ingestion
Oracle
Hadoop
Amazon S3
Amazon EC2
Amazon EKS
AWS Glue
Amazon SageMaker
Amazon Athena
Amazon Redshift
API Design
Microservices
Data Governance
DevOps

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