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Added 9 mins ago
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Javelin Technologies

Senior Data Engineer

Canada

Full-time

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Job details

Job type: Full-time
Experience: 8+ years experience in a relevant field, flexible for the right candidate.
Posting language: English
Posted: Nov 2, 2026

Original job description

PROFILE

TriMech is investing in a modern enterprise data platform - built on Microsoft Fabric - to create a trusted, scalable foundation for reporting, analytics, AI, and data-driven decision-making across the group. This role sits at the heart of that programme.

As Senior Data Engineer / Data Scientist, you will design, build, and operate the group's data ecosystem: integrating data from our core business systems, developing robust pipelines, establishing quality and governance standards, and delivering the advanced analytics and AI capabilities that shape strategic and operational decisions.

This is a hands-on, high-visibility role. You will work directly with executive leadership, business teams, and IT to turn raw data from platforms such as Salesforce, NetSuite, marketing systems, and bespoke applications into secure, governed, and genuinely useful insights. You will also help set the engineering standards, deployment practices, and support processes for the platform as it scales.

DUTIES AND RESPONSIBILITIES

Data platform engineering

Design and build scalable data pipelines, ingestion, transformation, and orchestration processes on Microsoft Fabric.
Develop the enterprise lakehouse architecture and data models that serve analytics, reporting, and AI use cases.
Integrate data across multiple applications via APIs and ETL tooling.
Optimise performance, reliability, and cost, and embed CI/CD and DevOps practices for platform deployments.

Business intelligence & analytics

Translate business requirements into analytical datasets, semantic models, and Power BI reporting across Sales, Finance, Marketing, Customer Success, Operations and more.
Build executive and board-level reporting datasets, and champion self-service analytics adoption.

Data science & AI

Develop forecasting, statistical, and predictive models using enterprise data assets.
Support AI and machine-learning initiatives and evaluate emerging technologies for practical business value.

Governance & quality

Implement data quality monitoring, validation, and master data management practices.
Establish cataloguing, lineage, and metadata management through Microsoft Purview, and support security, privacy, and regulatory compliance.

Stakeholder partnership

Work with leadership and data owners to improve definitions, consistency, and measurement frameworks.
Communicate technical concepts clearly to technical and non-technical audiences alike.

SKILLS AND REQUIREMENTS

A degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field - or equivalent practical experience.
8+ years experience in a relevant field, flexible for the right candidate.
Strong leadership skills
A strong track record designing and running enterprise-scale data pipelines and integrations across multiple applications.
Deep SQL expertise, data warehousing, and dimensional modelling, with experience of lakehouse and modern data architecture patterns.
Hands-on experience with Microsoft Fabric (or equivalent platform), or a strong Azure data estate (e.g. Azure Data Factory, Synapse) with the appetite to specialise in Fabric.
Power BI development, including semantic models.
Python and/or R for analytics and automation, plus source control and DevOps practices.
Applied experience in at least one of: predictive modelling, statistical analysis, forecasting, machine learning, or AI solution development.
Experience with business platforms such as Salesforce, NetSuite, and CRM/ERP integration patterns.
Microsoft, Azure, Fabric, or data engineering certifications.
Highly analytical and naturally curious, with strong attention to detail.
Ability to translate ambiguous business questions into clear data requirements and solutions
Comfortable moving between deep technical work and business conversations.
Able to work independently, manage competing priorities, and communicate with impact.
Passionate about data quality, governance, and continuous improvement.

COMPENSATION

OTE $154k - 165k per annum

PERKS AND BENEFITS

Hybrid Work Arrangements
Flex PTO
Competitive Group Benefits Plan
Perkopolis Membership Access – Employee perk and discount programs.
Wellness Program
Social Events

This opportunity is to fill an existing vacancy

TriMech is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including gender identity and sexual orientation), disability, age, national origin, or protect veteran status or any other protected status.

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More about this job

Responsibilities

Design, build, and operate TriMech’s enterprise data platform, including scalable pipelines, lakehouse architecture, integrations, data models, and governance practices. Deliver analytics, reporting, forecasting, and AI capabilities while partnering with executives, business teams, and IT.

Requirements

Requires a degree in a relevant field or equivalent practical experience, 8+ years of relevant experience, and a strong background in enterprise data pipelines, SQL, data warehousing, and modern data architecture. Candidates should have experience with Microsoft Fabric or an equivalent Azure platform, Power BI, Python and/or R, applied analytics or AI, and business systems such as Salesforce or NetSuite.

Skills

Microsoft Fabric
Data Engineering
Data Pipeline Development
SQL
Data Warehousing
Dimensional Modeling
Lakehouse Architecture
Power BI
Python
R
Data Science
Predictive Modeling
Machine Learning
Data Governance
Data Quality Management
DevOps

Benefits

Hybrid Work Arrangements
Flexible Paid Time Off
Competitive Group Benefits Plan
Perkopolis Membership
Wellness Program
Social Events

Visa sponsorship

Not detected in the job text

Keywords

Microsoft Fabric
Azure Data Factory
Azure Synapse
Microsoft Purview
Power BI
Salesforce
NetSuite
SQL
Python
R
Enterprise Data Platform
Data Pipelines
Data Integration
ETL
Lakehouse Architecture
Data Warehousing
Dimensional Modeling
Semantic Models
Data Orchestration
CI/CD
DevOps
Data Governance
Data Quality
Master Data Management
Metadata Management
Data Lineage
Predictive Modeling
Forecasting
Machine Learning
Artificial Intelligence

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