Sr. Data Analyst -1806 (Asset Management)

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:

1. 7+ years of experience working in data‑driven organizations on large‑scale, end‑to‑end data

initiatives.

2. 5+ years of hands‑on experience building data platforms, applications, and pipelines using

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

3. 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.

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

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

Redshift.

6. 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.