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Added 9 mins ago
O
Analyste-programmeur(se) full stack
Onepoint
Montreal, QC · Quebec, QC
- Full-time
Wepoint is the architect of major transformations for businesses and public sector organizations.
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- Full-time
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- Full-time
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- Full-time
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- Full-time
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Added 23 mins ago
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Data & Analytics Solutions Architect
J&M Group
Canada
- Full-time
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Added 23 mins ago
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Data Architect - Big Data & Analytics
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- Full-time
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Added 24 mins ago
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University of Toronto
Toronto, ON
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Added 54 mins ago
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- Full-time
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- Full-time
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Altis Technology
Toronto, ON · Greater Toronto Area, Canada
- $135,000 to $155,000 CAD / year
- Full-time
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- Full-time
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Conseiller(ère) en ingénierie de données intermédiaire (R22 -VIM/VNA) - Qualité des données
Wepoint
Montreal, QC · Quebec, QC
- Full-time
Wepoint is the architect of major transformations for businesses and public sector organizations.
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Conseiller(ère) en ingénierie de données - Qualité des données
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Added 2 hours ago
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Stacktics

Head of Data Systems (Google Stack)

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 8, 2026
Posting language: English
Posted: Oct 9, 2026

Original job description

The Head of Data Systems (Google Stack) will play a key role at Stacktics, required to help create and maintain industry-leading quality and efficiency of service and software delivery.

Stacktics will rely on the Head of Data Systems with ownership of the Data Systems function including mentoring and support for our team of engineers, developers, marketing analysts and data scientists. The successful candidate will be expected to meet and exceed Stacktics' quality standards, while helping the organization rapidly expand into increasingly complex application development, data engineering, and related workflows.

KEY RESPONSIBILITIES

Ownership of Stacktics' Data Systems Business Unit

Build and grow your team's capabilities and expertise to be truly platform-agnostic, ever-adapting based on opportunity and business direction
Lead thorough audits of clients'/prospects' Data Systems, and other associated platforms and technologies as applicable including performance and cloud cost-efficiency
Provide proactive recommendations, identifying areas of opportunity and/or improvement for clients based on their underlying business objectives and goals
Maintain continuous focus on work output quality and reliability, acting as the champion of customer satisfaction in a proactive manner and as the final escalation point for technical and delivery issues that cannot be resolved at the Technical Lead level
Act as Stacktics' primary Data Systems expert, ensuring to maintain and continuously grow personal expertise, and sharing information with other Stacktics team members, client stakeholders and prospects
Collaborate with, support, and work closely with cross-functional units to ensure efficient workflow, and realize cross-functional opportunities and enhancements
Maintain responsibility for the Business Unit's growth and success, continuously developing existing engagements, optimizing resourcing and prospecting
Be dedicated to the success and happiness of your team members, optimizing workflow, enabling their personal growth, and acting as a strong team leader overall

Instilling Development Best Practices and Skills/Procedures Advancement

Establishing, maintaining and evolving DevSecOps best practices and tools, and continuously keeping them aligned with current industry best practices and procedures
Understanding, implementing and automating security controls, governance processes, and compliance validation frameworks
Contributing to deployment tooling within the Stacktics team
Contributing to version control technology frameworks and creating/implementing working processes within the Data Systems team, with tools such as Git or SVN
Own and continuously improve the practice's AI coding standards, the AI coding constitution (CLAUDE.md, GEMINI.md, .cursorrules), PR checklists, and slash commands keeping them current as tools, clients, and the team's needs evolve

Leading in the Software 3.0 Era

AI tools have changed how fast engineering work gets produced. Your job is to make sure that speed shows up as sounder architecture and higher-quality delivery - not just faster shipping of the same judgment gaps.

Recalibrate how the team scopes and estimates work as AI tooling changes what can actually be delivered in a sprint, so timelines and resourcing plans reflect real AI-era delivery speed
Set architecture and coding standards that assume engineers are using AI assistants daily - code review habits, eval frameworks, and quality gates sized to the failure modes of AI-assisted development, not just its speed
Continue evolving Stacktics' AI Development Lifecycle (ADLC) - our AI-native answer to SDLC - piloting new stages against real engagements and driving adoption across the team
Be an active daily user of AI coding assistants yourself, and bring that firsthand experience into how standards and review practices are set for the team
Lead Stacktics’ technical team members through the integration into Agentic AI-first working patterns, and beyond

Code Productization

Migrating the delivery of the most common/universally applicable solutions from custom projects to formally productized software solutions
Advocating for building repeatability, scalability and standardization into how the Stacktics Data Systems team approaches all work, in order to enable the future migration to productization as a general rule

Data Engineering-Specific Responsibilities

Participate in continuous delivery pipelines to fully automate deployment of the highly available cloud platform that supports multiple projects
Design and develop ETL workflows and datasets to be used in data visualization tools
Write complex SQL queries with multiple joins to automate and manipulate data extracts
Perform end to end Data Validation to maintain accuracy of data sets
Build tools for deployment, monitoring and operations
Troubleshoot and resolve issues in the development, test and production environments
Develop re-usable processes that can be leveraged and standardized for multiple instances
Prepare technical specifications and documentation for projects
Stay up to date on relevant technologies, plug into user groups, understand trends and opportunities to ensure we are using the best possible techniques and tools
Understand, implement, and automate security controls, governance processes, and compliance validation

Contribution to Corporate Strategy

Actively and proactively play a key role in steering Stacktics and affiliated companies, considering market developments, competitive maneuvers, unique opportunities, etc.
You will be expected to both bring new ideas to the table and assist other corporate leaders in vetting/developing concepts and tactics
Identification and tracking of performance, coaching, training needs, and motivating members of the Data Systems team - including Senior Technical Leads. Directly or indirectly responsible for hiring, terminating and owning performance evaluations for direct reports and the Data Systems group

Company-Wide Responsibilities

Maintain and exceed client satisfaction with Stacktics’ deliverables, day-to-day work and overall value as a partner
Adapt to ever-changing client needs and expectations
Maintain dedication toward achieving excellence in Stacktics’ delivery against client needs, and overall success as an organization
Ability to provide clear guidance and support for advanced problem solving and system design to large teams at enterprise-level client companies, aiding the evolution of their digital practices

QUALIFICATIONS

Deep expertise in building and managing large-scale data systems on cloud platforms, with a strong preference for Google Cloud Platform (GCP) services
Python, SQL and Cloud Computing
10+ years experience in Data Engineering, including 6+ years in technical leadership or management roles, with experience managing other leads (e.g., Technical Leads or engineering managers).
Strong understanding of and direct experience with managing a team operating in a “Software 3.0” model (Agentic AI-first)
Active user of AI coding assistants (Copilot, Cursor, Claude Code, or equivalent), and fluent in what they change about estimation, architecture, and review
Understanding of digital ecosystems including online data collection, cloud systems and analytics tools (Google Stack, Facebook, Salesforce, Adobe Suite etc.) a strong asset
Strong technical understanding of a range of marketing concepts such as cookie-based data collection, setting and leveraging audience segments, attribution modelling, AB/N & multivariate is an asset
Excellent written & verbal communication skills are essential; candidate should be comfortable presenting and participating in group discussions of concepts with internal and external stakeholders
Candidate must exhibit an analytical, detail-oriented approach to problem solving
Experience with Jira / Atlassian project management tools is an asset

Preferred Qualifications

Google Cloud certifications (e.g., Professional Cloud Architect, Professional Data Engineer) are a strong plus.
Prior experience in a consulting environment, managing and delivering projects for multiple clients concurrently.

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More about this job

Responsibilities

Lead the Data Systems business unit, managing and developing the team while overseeing client audits, technical delivery, data engineering, security practices, and customer satisfaction. Advance AI-first engineering practices, productize repeatable solutions, and contribute to business growth and corporate strategy.

Requirements

Requires 10+ years of data engineering experience, including 6+ years in technical leadership or management, with experience managing technical leads or engineering managers. Candidates should have deep cloud data systems expertise, preferably with Google Cloud Platform, strong Python and SQL skills, and hands-on experience with AI coding assistants and AI-first engineering practices.

Skills

Data Engineering
Google Cloud Platform
Python
SQL
Cloud Computing
Technical Leadership
Team Management
ETL Workflows
DevSecOps
AI-Assisted Development
Software Architecture
Data Validation
Security Controls
Continuous Delivery
Project Management

Visa sponsorship

Not detected in the job text

Keywords

Google Cloud Platform
Python
SQL
Cloud Computing
Data Engineering
ETL
Data Validation
DevSecOps
Continuous Delivery
Git
SVN
Jira
Atlassian
AI Coding Assistants
Agentic AI
AI Development Lifecycle
Software Architecture
Security Controls
Governance
Compliance Validation
Cloud Cost Optimization
Marketing Analytics
Audience Segmentation
Attribution Modeling
A/B Testing
Multivariate Testing
Google Cloud Professional Cloud Architect
Google Cloud Professional Data Engineer
Productization
Consulting

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