Senior Data Engineer to architect and implement enterprise data solutions using Snowflake and cloud-native technologies - 1806

Senior Data Engineer to architect and implement enterprise data solutions using Snowflake and cloud-native technologies - 1806

Location: Downtown Toronto - Hybrid - Onsite Tuesday, Wednesday, Thursday

As a Senior Data Engineer, you will be a key contributor to enterprise data platform strategy, enabling self-serve analytics, scalable data products, and robust data governance across 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.

Must Haves:

• 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 .
• 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.
• Bachelors/ master's degree in computer science or a related technical field.

Nice to Have:

• Experience with data visualization tools (Power BI, Tableau)

Responsibilities:

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

Data Marketplace & Integrations

• Evaluate and implement system integrations supporting vision for data-as-a-product and enterprise data discovery.
• 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.

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.

Duration: 12 months to start