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Added 4 mins ago
Software Engineer, Full-Stack - Agents Cross-FA
Superhuman
Toronto, ON
$125,000 to $130,000 CAD / year
Full-time
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Data Engineer
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Full-time
The Data Engineer plays a hands-on role by preparing and integrating the data foundations that AI solutions depend on. This includes building ingestion pipelines, managing data stores,…
Added 2 hours ago
Thanks for visiting our Job Board. Please review our open positions and apply to the positions that match your qualifications.
Evertz
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GEI Consultants, Inc.

Data Engineer

Vaughan, ON, Canada

Pay: Pay Range For This Position: $90,000.00 – $150,000.00/year
Job type: Full-time
Apply by: Oct 17, 2026
Experience: 4+ years of data engineering experience, with demonstrated ability to build and operate production data pipelines.
Posting language: English
Posted: Apr 7, 2026

Apply About employer

Applications open in a new tab.

Original job description

Description

Your role at GEI.

The Data Engineer is responsible for designing, building, and maintaining the data pipelines and integrations that power GEI’s AI solutions and digital initiatives. This role focuses on ensuring enterprise data is accessible, reliable, and governed so that AI capabilities can be deployed and scaled with confidence.

The Data Engineer plays a hands-on role by preparing and integrating the data foundations that AI solutions depend on. This includes building ingestion pipelines, managing data stores, implementing quality and governance controls, and supporting retrieval patterns such as RAG. This role works closely with AI Engineers, solution architects, and platform teams to ensure data infrastructure is production-ready, secure, and aligned with GEI standards.

Essential Responsibilities & Duties

Design, build, and maintain data pipelines that ingest, transform, and deliver enterprise data to AI solutions and business applications.
Develop and manage integrations across enterprise data sources using APIs, Graph connectors, event-driven architectures, and batch/streaming patterns.
Build and maintain data stores and indexing infrastructure that support retrieval-augmented generation (RAG) and other AI consumption patterns.
Implement data quality, validation, and lineage controls to ensure accuracy and trustworthiness of data feeding AI workflows.
Support and optimize data models underpinning Power BI dashboards and AI-enabled analytics.
Collaborate with AI Engineers to define data contracts and ensure pipeline outputs meet solution requirements for schema, latency, and freshness.
Instrument data pipelines for monitoring, alerting, cost control, and performance optimization.
Implement data governance and security controls including access management, encryption, and compliance with organizational data policies.
Identify data-related risks and support mitigation strategies in collaboration with architecture and platform teams.

Minimum Qualifications

4+ years of data engineering experience, with demonstrated ability to build and operate production data pipelines.
Proficiency in Python and SQL; experience with PySpark or Spark is strongly preferred.
Experience with Azure data services, including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, and Azure SQL.
Familiarity with Azure AI Search, Cosmos DB, or similar services used to support AI retrieval and storage patterns.
Experience building and managing ETL/ELT pipelines with structured, semi-structured, and unstructured data sources.
Knowledge of data modeling, schema design, and indexing strategies for both analytical and AI workloads.
Familiarity with infrastructure-as-code and CI/CD practices for data pipeline deployment (e.g., Terraform, Azure DevOps).
Knowledge of data governance principles, including data cataloging, lineage, access control, and privacy requirements.
Knowledge of security best practices for data solutions, including encryption at rest and in transit, role-based access control, and private networking.
Experience with Databricks, including Delta Lake and Unity Catalog, is a plus.
Prior experience in professional services, engineering, or construction environments is a plus.
Azure or Databricks certifications (e.g., Azure Data Engineer Associate, Azure Solutions Architect Expert, Databricks Data Engineer Professional) are a plus.

We are GEI.

Some of the world’s most pressing problems – from climate change to sustainable development, to critical infrastructure and the future of our energy supply – need our brightest and diverse minds working together to create safer, more resilient communities for tomorrow.

We are technical experts, collaborators, and entrepreneurs who draw from diverse backgrounds to solve our clients’ most complex challenges.

With several offices across North America, we offer a range of engineering, science, and technical consulting services. Our range of expertise, project types, and culture make us the choice for top talent in the AEC industry. See all our office locations here.

Employee-owned. Employee-focused.

As an employee-owned company, our employees support our flat leadership structure, have a say in how our business operates and benefit from our financial success. We are committed to employee growth with career development opportunities, competitive total rewards, a well-being program, flexible work arrangements and more. Our company culture is driven by our 4 Cs – we are Client-Centered, Curious, Collaborative, and Community Minded – which support our focus on sustainability, safety, diversity, equity and inclusion. Get to know us better by visiting GEI’s career site here.

GEI’s Total Rewards Package Includes

Market-Competitive Compensation, including Eligibility for an Annual Performance Bonus
Pay Range For This Position: $90,000.00 – $150,000.00/year
Comprehensive Benefits Program, including Medical, Dental, Vision, Life, Disability and More
Well-Being Program and Paid Parental Leave
Commuter Benefits
Hybrid Work Schedules and Cell Phone Stipends
GEI University (GEIU) with Continuing Education Assistance and Tuition Reimbursement
Connecting Conversation Program with a Focus on Professional Development and Opportunities for Advancement
Support and Financial Rewards for Publication Awards, Professional Dues, and Professional Licenses
Paid Holidays and Generous Paid Time Off Program
Rewards and Recognition
GEI-Funded Profit Sharing and 401(k)
Opportunity to be an Owner and Shareholder (Learn more here)
A Vibrant Culture that is Focused on Partnership, Sustainability, Giving Back to Our Communities and Diversity, Equity and Inclusion
And More…

Physical Requirements

WORK ENVIRONMENT

Functional Demands

Sedentary

x

Light

Medium

Other

Activity Level Throughout Workday (check one per row)

Physical Activity Requirements

Occasional

(0-35% of day)

Frequent

(33-66% of day)

Continuous

(67-100% of day)

Not Applicable

Sitting

x

Standing

x

Walking

x

Climbing

x

Lifting (floor to waist level) (in pounds)

x

Lifting (waist level and above) (in pounds)

x

Carrying objects

x

Push/pull

x

Twisting

x

Bending

x

Reaching forward

x

Reaching overhead

x

Squat/kneel/crawl

x

Wrist position deviation

x

Pinching/fine motor skills

x

Keyboard use/repetitive motion

x

Taste or smell (taste=never)

x

Talk or hear

x

Accurate 20/40

Very Accurate 20/20

Not Applicable

Near Vision

x

Far Vision

x

Yes

No

Not Applicable

Color Discrimination

Sensory Requirements

Minimal

Moderate

Accurate

Not Applicable

Depth perception

x

Hearing

x

Environment Requirements

Occupational Exposure Risk Potential

Reasonably Anticipated

Not Anticipated

Blood borne pathogens

x

Chemical

x

Airborne communicable diseases

x

Extreme temperatures

x

Radiation

x

Uneven surfaces or elevations

x

Extreme noise levels

x

Dust/particulate matter

x

Other (exposure Risks)

Usual workday hours:

x

8

10

12

Other work hours

GEI is an AA/equal opportunity employer, including disabled and veterans.

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More about this job

Responsibilities

Design, build, and operate secure, reliable data pipelines and integrations that prepare enterprise data for AI solutions, business applications, and analytics. Maintain data stores and retrieval infrastructure, implement quality, governance, and security controls, and collaborate with AI and platform teams to monitor and optimize production data systems.

Requirements

Requires at least four years of data engineering experience, proficiency in Python and SQL, and experience building production ETL/ELT pipelines with varied data sources. Candidates should have experience with Azure data services, data modeling, governance, security, and CI/CD or infrastructure-as-code practices; Spark, Databricks, relevant certifications, and professional services or engineering experience are preferred or advantageous.

Skills

Data Engineering
Python
SQL
PySpark
Apache Spark
Azure Data Factory
Azure Synapse Analytics
Azure Data Lake Storage
Azure SQL
Azure AI Search
Cosmos DB
ETL/ELT
Data Modeling
Data Governance
Infrastructure as Code
CI/CD

Benefits

Annual Performance Bonus
Medical Insurance
Dental Insurance
Vision Insurance
Life Insurance
Disability Insurance
Well-Being Program
Paid Parental Leave
Commuter Benefits
Cell Phone Stipend
Continuing Education Assistance
Tuition Reimbursement
Professional Development
Paid Holidays
Paid Time Off
Profit Sharing
401(k)
Employee Ownership
Flexible Work Arrangements

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Python
SQL
PySpark
Apache Spark
Azure Data Factory
Azure Synapse Analytics
Azure Data Lake Storage
Azure SQL
Azure AI Search
Cosmos DB
Databricks
Delta Lake
Unity Catalog
ETL/ELT
Data Pipelines
APIs
Microsoft Graph Connectors
Event-Driven Architecture
Batch Processing
Stream Processing
Retrieval-Augmented Generation
Power BI
Data Modeling
Data Quality
Data Lineage
Data Governance
Terraform
Azure DevOps
Role-Based Access Control

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