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.
