Jobs in Georgetown, ON and nearby

Jobs within 25 km of Georgetown, ON, Canada. Nearby towns and cities are included. Distances are straight-line, not driving distances.

22,301 listings · 4,076 employers Counted Nov 3, 2026. How we count

About these jobs

Employers hiring include Loblaw Companies Limited (530 listings), Shoppers Drug Mart (445 listings), Walmart Canada (420 listings).

Common roles: Retail sales associate, Sales representative, Project manager.

4,294 of these listings include employer-provided pay. Open a job to see its currency and pay period.

Advertised starting pay
Pay period	Median starting pay	Listings
CAD / hour	30.00	2,126
CAD / year	80,000.00	1,919
USD / hour	20.60	77
USD / year	90,000.00	56

Employer-listed minimums from at least 10 listings per currency and pay period. These are advertised starting amounts, not employee salaries. Jobs without a minimum and unusual amounts are excluded.

Workplace classifications: 0% remote, 18% hybrid, 82% on-site, 0% not specified. Hybrid and on-site classifications may be inferred from descriptions. Check the original ad.

Based on the dated count above. Listings can change. How we count

Jobs in Georgetown, ON and nearby

Within 25 km

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Added 2 hours ago
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RAPS Consulting Inc

Data Lineage / Meta data Engineer

Mississauga, ON, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Dec 3, 2026
Posting language: English
Posted: Nov 3, 2026

Original job description

Data Lineage / Meta data Engineer

Location : Mississauga, Canada (onsite)

Role Summary

Developer focused on data lineage to build systems that parse and analyze large, multi-language codebases and automatically generate accurate data lineage. The role pairs strong Python engineering with hands-on Gen AI/LLM work and ownership of build, deployment, and delivery pipelines. The emphasis is on clean, efficient, well-architected design - systems that are correct, performant, and maintainable as they scale.

What You'll Do

Design and build engines that parse multiple programming and query languages to extract accurate, column-level data lineage.
Build Gen AI/LLM-powered retrieval and assistant capabilities on top of lineage and metadata.
Develop backend services and the interfaces that expose them, from data processing through to user-facing views.
Own the delivery pipeline - build, test, deployment, and production support across environments.

Design Principles We Value

Simplicity first - favor the simplest design that solves the problem; avoid unnecessary complexity and premature abstraction.
Separation of concerns - clear module boundaries, single-responsibility components, and well-defined interfaces so pieces can evolve independently.
Correctness and determinism - prefer predictable, testable behavior; ground AI outputs in verifiable data rather than guesswork.
Performance-aware design - think about time/space complexity, memory footprint, and efficient data structures and algorithms up front.
Scalability and extensibility - design so new languages, sources, and capabilities can be added without rewrites.
Robustness - graceful error handling, fault isolation, and defensive design so one bad input can't take the system down.
Readability and maintainability - code and designs the next engineer can understand, extend, and debug.
Reuse over duplication - shared models and common abstractions instead of repeated logic.

Required Skills

Strong Python development with solid object-oriented and functional design skills.
Software engineering fundamentals: data structures, algorithms, and complexity analysis.
Data lineage / data flow analysis: parsing and analyzing source code (AST-based and pattern-based static analysis) and comfort reading multiple languages.
Hands-on Gen AI/LLM experience: prompt design, tool/function calling, and agent orchestration.
Understanding of retrieval-augmented generation and vector/semantic search concepts.
Experience designing APIs and backend services, plus the front-end fundamentals to build usable interfaces.
Pipeline and deployment experience: build/test automation, CI/CD, and releasing across environments.
Data manipulation and transformation skills.

Nice to Have

Graph algorithms and traversal techniques for dependency/lineage tracing.
Data governance, metadata management, and data cataloging concepts.
Experience designing systems for long-running or asynchronous workloads.
Infrastructure automation and deployment tooling.

Key Responsibilities

Translate ambiguous requirements into clean, efficient, well-structured designs.
Extend parsing and analysis capabilities to new languages and frameworks without compromising architecture.
Design and productionize Gen AI/LLM and retrieval features that are accurate and grounded in real data.
Build and maintain deployment pipelines; support delivery across environments.
Write tests and maintain quality across the development lifecycle.
Collaborate on design reviews and raise the engineering bar for the team.

Apply About employer

More about this job

Responsibilities

Build systems that parse multiple programming and query languages to generate accurate, column-level data lineage, and develop LLM-powered retrieval and assistant capabilities grounded in metadata. Design backend services and user-facing interfaces, own build and deployment pipelines, and support testing, production delivery, and ongoing quality.

Requirements

Requires strong Python engineering, software design fundamentals, and experience parsing and analyzing source code for data lineage. Also requires hands-on Gen AI/LLM experience, knowledge of retrieval-augmented generation and semantic search, API and backend development skills, and experience with CI/CD and deployment.

Skills

Python
Data Lineage
Static Code Analysis
Abstract Syntax Trees
Gen AI
Large Language Models
Prompt Design
Tool Calling
Agent Orchestration
Retrieval-Augmented Generation
Vector Search
Backend Services
API Design
CI/CD
Data Transformation
Graph Algorithms

Visa sponsorship

Not detected in the job text

Keywords

Python
Data Lineage
Metadata Management
Column-Level Lineage
Source Code Parsing
Static Analysis
Abstract Syntax Trees
Programming Languages
Query Languages
Generative AI
Large Language Models
Prompt Design
Function Calling
Agent Orchestration
Retrieval-Augmented Generation
Vector Search
Semantic Search
APIs
Backend Services
Data Transformation
Data Structures
Algorithms
Graph Algorithms
CI/CD
Build Automation
Test Automation
Deployment Pipelines
Asynchronous Workloads
Data Governance
Data Cataloging

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