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Added 1 min ago
Senior Test Engineer
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Ottawa, ON
Full-time
Designs, develops, and implements cost-effective methods of testing and troubleshooting systems and equipment for all phases of product development and manufacturing. Prepares test and…
Added 15 mins ago
Quality Engineer
AgileGrid Solutions
Canada
Full-time
We are seeking a highly skilled and detail-oriented Quality Engineer to join our dynamic team. In this role, you will be instrumental in maintaining and enhancing the quality standards of…
Added 15 mins ago
Senior Piping Designer CAN
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Calgary, AB · Greater Calgary Metropolitan Area
Full-time
Quality review PFDs and P&IDs from verbal or written description from the design engineer.
Added 15 mins ago
Sr SAP SuccessFactors Engineer - Toronto / Vancouver (Canada)
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Vancouver, BC
Contract
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Added 15 mins ago
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Toronto, ON
Champions a customer focused culture to deepen client relationships and leverage broader Bank relationships, systems and knowledge.
Added 31 mins ago
Software Engineering Developer, DevOps
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$85,000 to $110,000 CAD / year
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Added 45 mins ago
Maintenance Power Engineer 3rd Class - BC Children's & Women's Hospital
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Added 45 mins ago
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Added 45 mins ago
Software Engineering Developer, DevOps
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Flexkube Lab Inc.

Data Engineer

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Job type: Contract
Apply by: Mar 22, 2027
Experience: 3+ years of experience in Data Engineering.
Posting language: English
Posted: Sep 23, 2026

Apply About employer

Applications open in a new tab.

Original job description

Data Platform Engineering

•

Design, build, and support scalable data pipelines using Python, Spark, and Databricks.

•

Modernize legacy data processing workloads and migrate existing pipelines to secure cloud-native platforms.

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Implement data quality, monitoring, observability, and operational controls.

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Optimize performance, scalability, reliability, and cost efficiency of data workloads.

Data Ingestion & Integration

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Build and maintain ingestion pipelines for structured and unstructured data sources.

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Connect to APIs to ingest data from internal and external systems.

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Build and maintain batch-processing pipelines, with occasional work on streaming pipelines.

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Integrate data from SharePoint, document repositories, enterprise applications, and cloud platforms.

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Follow established security and data-handling practices when connecting to sources, managing pipeline credentials, and writing data.

Document Intelligence & Automation

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Develop document extraction, classification, and metadata enrichment pipelines.

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Support AI-assisted processing of large-scale document repositories.

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Automate data transformation and enrichment workflows.

Platform Modernization

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Implement migration and refactoring of existing data assets and pipelines.

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Apply software engineering practices including CI/CD, automated testing, and code reviews.

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Understand the purpose and broader context of assigned work, identify gaps or assumptions, and suggest changes or alternative approaches when they would better achieve the intended outcome.

Engineering Excellence

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Collaborate with architects, tax subject matter experts, developers, and platform teams.

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Use AI-assisted development tools such as Codex to build data pipelines, and review and test the resulting code.

Required Qualifications

Technical Skills

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3+ years of experience in Data Engineering.

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Strong Python development experience.

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Strong Apache Spark and PySpark experience.

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Experience with Databricks.

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SQL expertise and data modeling experience.

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Experience building, testing, deploying, and troubleshooting production ETL/ELT pipelines.

Software Engineering

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Experience with Git-based source control and CI/CD pipelines.

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Experience consuming REST APIs for data ingestion, including authentication, pagination, and handling failures.

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Experience writing automated tests for data pipelines.

Preferred Qualifications

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Experience with Azure cloud services.

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Experience with document-processing or intelligent document extraction solutions.

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Experience using AI-assisted development tools such as Codex, GitHub Copilot, or similar developer productivity platforms.

Desired Characteristics

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Strong problem-solving and troubleshooting skills.

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Exercise judgment about when to proceed independently, ask for clarification, or challenge the proposed approach.

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Comfortable analyzing unfamiliar codebases and modernizing legacy implementations.

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Ability to identify and explain improvements to existing data pipelines.

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Strong communication and collaboration skills.

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Willingness to learn new tools and data sources.

Success Criteria

Success in this role means:

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Modernize key Spark/Python workloads.

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Improve security, maintainability, and reliability of existing pipelines.

•

Deliver scalable ingestion and document processing capabilities.

•

Use AI-assisted development practices to deliver maintainable, tested pipeline code.

Apply About employer

More about this job

Responsibilities

Build, modernize, and support scalable Python, Spark, and Databricks data pipelines, including batch ingestion, API integrations, and document extraction and enrichment workflows. Improve pipeline security, quality, observability, performance, reliability, and cost efficiency while collaborating with architects, subject matter experts, developers, and platform teams.

Requirements

Requires at least three years of data engineering experience, strong Python, Spark/PySpark, Databricks, SQL, and data modeling skills, and experience delivering production ETL/ELT pipelines. Candidates should also have Git and CI/CD experience, be able to consume REST APIs and write automated tests, and demonstrate strong troubleshooting and collaboration skills.

Skills

Python
Apache Spark
PySpark
Databricks
SQL
Data Modeling
ETL/ELT Pipelines
REST APIs
Data Ingestion
CI/CD
Automated Testing
Git
Azure
Document Processing
Data Quality
Data Observability

Visa sponsorship

Not detected in the job text

Keywords

Python
Apache Spark
PySpark
Databricks
SQL
Data Engineering
Data Pipelines
ETL/ELT
Data Modeling
REST APIs
API Authentication
Batch Processing
Streaming Pipelines
Data Ingestion
Data Integration
Document Extraction
Document Classification
Metadata Enrichment
Document Processing
Cloud-Native Platforms
Azure
Git
CI/CD
Automated Testing
Code Reviews
Data Quality
Monitoring
Observability
Pipeline Security
Codex

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