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Added 2 mins ago
Data Engineer Sr
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Experience developing data solutions using Python, Scala, Java, or similar programming languages.
Added 1 hour ago
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Added 3 hours ago
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Senior Data Engineer
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Added 6 hours ago
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Added 1 day ago
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Added 1 day ago
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HOOPP (Healthcare of Ontario Pension Plan)

Senior Data Engineer

Toronto, ON, Canada

Pay: $103,000 to $153,000 CAD / year
Job type: Full-time
Apply by: Oct 25, 2026
Posting language: English
Posted: Sep 25, 2026

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Original job description

Why You’ll Love Working Here

high-performance, people-focused culture
our commitment that equity, diversity, and inclusion are fundamental to our work environment and business success, which helps employees feel valued and empowered to be their authentic selves
learning and development initiatives, including workshops, Speaker Series events and access to LinkedIn Learning, that support employees’ career growth
membership in HOOPP’s world class defined benefit pension plan, which can serve as an important part of your retirement security
competitive, 100% company-paid extended health and dental benefits for permanent employees, including coverage supporting our team's diversity and mental health (e.g., gender affirmation, fertility and drug treatment, psychological support benefits of $2,500 per year, parental leave top-up, and a health spending account).
optional post-retirement health and dental benefits subsidized at 50%
yoga classes, meditation workshops, nutritional consultations, and wellness seminars
the opportunity to make a difference and help take care of those who care for us, by providing a financially secure retirement for Ontario healthcare workers

Job Summary

HOOPP's Information Technology teams deliver innovative technology solutions to help build a stronger financial future for the healthcare community. As a Senior Data Engineer, you will design and build the data foundations (spanning structured and unstructured data on AWS) that turn raw information into trusted insight and AI-ready assets to support our teams in delivering on the pension promise.

Our Enterprise Data Platform team builds and operates the cloud data platform that powers analytics, reporting, and AI across HOOPP. As a Senior Data Engineer, reporting to the Senior Director, Enterprise Data Platform, you will build scalable pipelines on AWS across both structured and unstructured data, stand up the ingestion and retrieval patterns behind our emerging AI use cases, and set the engineering standards the broader data team builds on.

We cultivate a culture that emphasizes innovation, collaboration, practicality, and the courage to challenge the status quo. This role is well suited to someone who combines technical depth with curiosity, sound judgment, product thinking, systems thinking, and a willingness to test new ideas. You will look beyond immediate symptoms, identify underlying needs, and develop solutions that are secure, sustainable, and valuable in delivering the pension promise. Success in this role requires the ability to navigate ambiguity, ask thoughtful questions, and turn emerging technologies into practical solutions that deliver measurable business impact.

What You Will Do

Build the data foundations that power HOOPP’s AI ambitions by transforming structured data, documents, text, and other unstructured content into trusted, accessible assets that fuel AI models, search, and retrieval capabilities.
Take AI and analytics ideas from whiteboard to production with data scientists, AI engineers, and the business. We prototype fast, prove what works, and retire what doesn't.
Use Snowflake as a core data warehouse and AI platform, applying capabilities such as Cortex AI to support scalable analytics and emerging AI use cases.
Architect cloud-native pipelines on AWS that move structured and unstructured data at scale.
Shape our lakehouse on Amazon S3 by using open table formats, thoughtful data models, and metadata that makes the platform genuinely easy for others to build on.
Set the engineering standards the broader data team builds on, and raise the bar through design reviews, code reviews, and mentorship.
Bring engineering rigor to data through automated testing, infrastructure-as-code, and CI/CD that make releases boring and reliable.
Build quality, lineage, and observability into every pipeline from day one, so trust in the data is the default.

What You Will Bring

7+ years of data engineering experience, combined with 3+ years building production data solutions on AWS.
Hands-on depth with the AWS data stack - for example S3, Glue, Lambda, Athena, Step Functions, and EventBridge.
Hands-on experience with Snowflake, including its AI and generative AI capabilities (such as Cortex AI, Snowpark, and vector search).
Strong SQL and Python, with experience building distributed data processing at scale (Spark preferred).
Demonstrated experience working with unstructured data (documents, text, images, or audio) in support of AI or machine learning use cases.
Exposure to AI and generative AI data patterns such as embeddings, vector stores, and retrieval-augmented generation.
Experience with lakehouse architectures and open table formats (Iceberg, Delta, or Hudi), as well as dimensional modelling for analytics.
Working knowledge of infrastructure-as-code (Terraform or CloudFormation), Git, and CI/CD for data workloads.
Ability to navigate ambiguity, ask thoughtful questions, and turn emerging technologies into practical, measurable outcomes.
Strong communication skills, with the ability to explain technical trade-offs to non-technical partners and mentor other engineers.
Post-secondary education in computer science, engineering, or a related field; AWS Data Engineer or Solutions Architect certification is an asset

The expected annual base salary range for this role is: $103,000 - $153,000 CAD

The actual base salary offered to the successful candidate may vary based on multiple factors including, but not limited to, individual's expertise and level of experience applicable to the role they are being offered.

This role is eligible to participate in discretionary incentive plan(s), subject to the terms and conditions of the applicable incentive plan text.

This job is for an existing vacancy.

HOOPP may use artificial intelligence tools to assist in screening, assessing and selecting applicants for this position. These tools support our recruitment process but do not replace human judgment and decision-making.

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More about this job

Responsibilities

Build and operate scalable AWS data pipelines and lakehouse foundations for structured and unstructured data, supporting analytics, AI, search, and retrieval use cases. Establish engineering standards and reliable practices for testing, infrastructure as code, CI/CD, data quality, lineage, and observability, while mentoring engineers and collaborating with business and technical teams.

Requirements

Requires 7+ years of data engineering experience, including 3+ years building production data solutions on AWS, with hands-on expertise in AWS data services, Snowflake, SQL, Python, and distributed processing. Candidates should also have experience with unstructured data and AI/ML patterns, lakehouse architectures, infrastructure as code, Git, and CI/CD, along with strong communication skills; post-secondary education in a related field is required, and an AWS certification is an asset.

Skills

AWS Data Engineering
Snowflake
Python
SQL
Distributed Data Processing
Apache Spark
Unstructured Data Engineering
Generative AI
Vector Search
Retrieval-Augmented Generation
Lakehouse Architecture
Dimensional Modeling
Infrastructure as Code
CI/CD
Data Quality and Observability
Technical Mentorship

Benefits

Defined Benefit Pension Plan
Extended Health Benefits
Dental Benefits
Parental Leave Top-Up
Health Spending Account
Yoga Classes
Meditation Workshops
Nutritional Consultations
Wellness Seminars
Discretionary Incentive Plan

Visa sponsorship

Not detected in the job text

Keywords

AWS
Amazon S3
AWS Glue
AWS Lambda
Amazon Athena
AWS Step Functions
Amazon EventBridge
Snowflake
Cortex AI
Snowpark
Vector Search
Python
SQL
Apache Spark
Structured Data
Unstructured Data
Generative AI
Embeddings
Vector Stores
Retrieval-Augmented Generation
Lakehouse Architecture
Apache Iceberg
Delta Lake
Apache Hudi
Dimensional Modeling
Terraform
AWS CloudFormation
Git
CI/CD
Data Lineage

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