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HOOPP (Healthcare of Ontario Pension Plan)

Senior Data Solutions Engineer

Toronto, ON, Canada
CA ON Toronto, Canada

Pay: $103,000 to $153,000 CAD / year
Job type: Full-time
Experience: 5+ years of professional software development experience using languages such as Java, Python, C#, or C++.
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 Solution Engineer, you will help keep HOOPP's investment data ecosystem reliable, governed, and ready to evolve toward a shared enterprise data model.

Our DTS Operations team supports the investment data warehouse and the governed data models and transformation logic that represent HOOPP's investment book, positions, transactions, valuations, and market data. As a Senior Data Solution Engineer, reporting to the Senior Manager, Investment Data Operations, you will own outcomes from first detection through root-cause closure, helping ensure data is reliable for trading, investment operations, risk management, valuation, performance, and analytics.

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:

Evolve the investment data warehouse, pipelines and enterprise data model supporting HOOPP's investment book, market data, and downstream business processes.

Own the Detect -> Respond -> Prevent cycle across the platform stack, resolving incidents, completing root-cause analysis, and driving preventive actions to closure.

Investigate investment data issues across positions, transactions, securities, pricing, valuation, and market data, tracing end-to-end flows from source platforms to downstream consumers.

Create and validate changes to data models, business logic, and data feeds, while protecting data integrity, lineage, auditability, and ICFR controls.

Design and extend AI-assisted projects using Python, Jupyter notebooks, PowerShell, and alternative AI tools, with clear human validation and approval points.

Lead projects and provide long-term solutioning by solving the root cause of a problem and partnering with investment, risk, finance, operations, data management, and technology teams to deliver reliable data solutions, operational readiness, and sustainable production support.

Investigate platform, data pipeline and scheduling challenges using logs, scripts, execution reports, and system diagnostics.

Execute and enhance governance activities, including production release reconciliations, Quarterly Access Reviews, entitlement management, and privileged-access oversight.

Maintain and improve runbooks, monitoring, knowledge assets, enterprise job schedules, and operational workflows.

What you will bring:

5+ years of professional software development experience using languages such as Java, Python, C#, or C++.

Technical fluency across data platforms and operational systems, including Snowflake, Python, SAP HANA, PowerShell, AWS GLUE, and REST APIs, with knowledge of data pipelines, databases, job scheduling, columnar technologies, and production support.

Strong SQL, data analysis, critical thinking, and creative problem-solving skills to investigate issues, test assumptions and hypotheses, identify root causes, validate results, and develop sustainable solutions. Knowledge of investment products, investment strategies, portfolio theory, valuation models, risk models, and finance theory is an asset.

Proven experience creating AI agents, skills, or intelligent automation solutions, combined with the ability to think strategically, challenge existing approaches, solve complex problems, and translate emerging AI capabilities into practical business outcomes. Sound judgment to determine next steps, engage the right stakeholders, and balance urgency and quality with governance, compliance, and long-term reliability.

Accountability for outcomes and a continuous-improvement mindset, with the discipline to carry work through implementation, validation, documentation, and closure. This includes simplifying and automating processes, measuring results, and preventing recurrence.

Comfortable working across teams, with strong communication skills and the ability to translate complex technical concepts into clear, non-technical language.

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

The Senior Data Solutions Engineer will manage the investment data ecosystem, ensuring data reliability for trading, risk management, and analytics. They will lead the detection, response, and prevention cycle for data incidents while evolving data pipelines and enterprise models.

Requirements

Candidates must have 5+ years of professional software development experience with languages like Java, Python, C#, or C++. Proficiency in data platforms such as Snowflake, SAP HANA, and AWS Glue, along with strong SQL and analytical skills, is required.

Skills

Java
Python
C#
C++
Snowflake
SAP HANA
PowerShell
AWS Glue
REST APIs
SQL
Data analysis
Investment products
Portfolio theory
Valuation models
Risk models
AI automation

Benefits

Defined benefit pension plan
Extended health benefits
Dental benefits
Mental health support
Gender affirmation coverage
Fertility treatment coverage
Drug treatment coverage
Parental leave top-up
Health spending account
Yoga classes
Meditation workshops
Nutritional consultations
Wellness seminars
Learning and development initiatives
LinkedIn Learning access

Visa sponsorship

Not detected in the job text

Keywords

Data Solutions Engineer
Investment Data
Data Warehouse
Data Pipelines
Enterprise Data Model
Java
Python
C#
C++
Snowflake
SAP HANA
PowerShell
AWS Glue
REST APIs
SQL
AI Agents
Intelligent Automation
Root-cause analysis
Data Governance
Investment Operations
Risk Management
Valuation Models
Portfolio Theory
Finance Theory
Production Support
Data Integrity
Lineage
Auditability
ICFR Controls
Jupyter Notebooks

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