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

S.I. Systems Ltd.; Toronto; Hybrid; CAD 120,000 - 170,000; Full time

Job summary

S.I. Systems Ltd. is seeking a Senior Data Engineer in Downtown Toronto with hybrid work, onsite Tue-Thu. You will architect and implement enterprise data solutions powering self-serve analytics and data governance across portfolios.

You will mentor junior engineers, drive platform evolution, and collaborate with analysts and product teams to deliver secure, scalable data products using Snowflake and cloud-native technologies.

Qualifications

• 7-8 years of experience in asset management is mandatory.
• 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.
• Bachelor's/ master's degree in computer science or a related technical field.

Responsibilities

• 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.
• 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.
• 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.
• Establish and enhance DevOps practices to improve developer experience and time-to-market.
• Advocate for and implement strong data governance, quality, and reliability practices.
• 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.

Skills

Python

Java

Scala

SQL

Asset management

Data governance

Education

Bachelor's degree in Computer Science

Master's degree in Computer Science

Tools

Snowflake

AWS

Azure

GCP

S3

EC2

EKS

Glue

SageMaker

Athena

Redshift

Power BI

Tableau

Job description

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

Disclaimer:
AI may be used in evaluating candidates.
This posting is for an existing vacancy.