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Azure Data Engineer

Amphenol ICC

Markham

On-site

CAD 90,000 - 120,000

Full time

14 days ago

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Job summary

A leading company in the interconnect products industry is seeking an experienced Azure Data Engineer to join their IT Infrastructure Team in Markham. This role focuses on architecting and managing scalable data infrastructure in Azure, collaborating with various teams to ensure secure and efficient data handling and analytics.

Benefits

Comprehensive health, dental, and vision coverage
Health Care Spending Account
Pension Plan
Progressive employee incentive plans
Opportunities for professional growth
Company Recreation Club with activities and events

Qualifications

  • 3+ years of experience in Azure data services.
  • Experience in integrating ERP data and other business systems.
  • Strong problem-solving and debugging skills.

Responsibilities

  • Design, deploy, and manage cloud data infrastructure components in Azure.
  • Develop, optimize, and maintain scalable ETL/ELT data pipelines.
  • Monitor data pipeline performance and ensure data governance.

Skills

Azure Data Factory
SQL
Python
PowerShell
DevOps

Education

College Diploma or University Degree in Computer Science
Information Technology
Data Science

Tools

Azure SQL
Azure Data Lake
Azure Synapse Analytics
Git
Terraform

Job description

Summary of Business:

Amphenol (www.amphenol.com) is a Fortune 500 company and one of the largest manufacturers of interconnect products in the world. We design, manufacture, and market electrical, electronic, and fiber optic connectors, coaxial and flat-ribbon cable, and interconnect systems. The primary end markets for our products include communications and information processing, aerospace, military electronics, automotive, and other industrial applications.

Job Description:

We are looking for an experienced Azure Data Engineer to join our IT Infrastructure Team. This individual will be responsible for architecting, building, and managing scalable data infrastructure in Azure. The focus of this role is on deploying and maintaining cloud-based data pipelines, ingestion frameworks, and preparing structured data environments for downstream analytics teams.

This role involves working closely with Data Analysts, the ERP Team, and other business units to ensure the right data is securely and efficiently collected, transformed, and made accessible. Ideal candidates will have a strong background in Azure cloud services, data engineering, and DevOps concepts, and enjoy building the infrastructure foundation for modern data platforms.

Roles & Responsibilities:

  • Design, deploy, and manage cloud data infrastructure components in Azure (e.g., Data Lake Storage, Data Factory, Synapse, Azure SQL).
  • Develop, optimize, and maintain scalable and reusable ETL/ELT data pipelines and workflows.
  • Ingest structured and unstructured data from a variety of sources, including ERP systems, APIs, and flat files.
  • Collaborate with Data Analysts to understand data requirements and prepare clean, curated datasets for analysis and reporting.
  • Ensure data governance, quality, privacy, and security standards are enforced across the data lifecycle.
  • Automate data infrastructure provisioning using Infrastructure-as-Code principles (e.g., Bicep, ARM templates, or Terraform).
  • Monitor data pipeline performance, reliability, and cost-efficiency.
  • Work with network/security teams to ensure proper firewall rules, identity access management, and hybrid data connectivity.
  • Maintain documentation for architecture, data lineage, data dictionaries, and pipeline workflows.

What You Bring to the Table:

Education:

  • College Diploma or University Degree in Computer Science, Information Technology, Data Science, or a related field.

Experience:

  • 3+ years of experience in Azure data services and business intelligence development.

Technical Skills:

  • Advanced proficiency in Azure Data Factory, Azure Data Lake, Azure SQL, and Azure Synapse Analytics.
  • Strong SQL skills for data transformation, optimization, and modeling.
  • Scripting experience in Python or PowerShell for automation and orchestration tasks.
  • Familiarity with DevOps tools, CI/CD pipelines, version control (Git), and IaC tooling.
  • Experience integrating ERP data and other business systems using APIs or connectors.
  • Working knowledge of networking concepts (firewalls, DNS, VNETs) and hybrid cloud integrations.
  • Bonus: Experience with Databricks, Delta Lake, or event-driven architectures (e.g., Event Hub, Kafka).

Certifications (Preferred):

  • Microsoft Certified: Azure Data Engineer Associate
  • Microsoft Certified: Power BI Data Analyst Associate
  • Microsoft Certified: Azure Administrator Associate
  • Microsoft Certified: Power BI Data Analyst

Other Skills:

  • Strong problem-solving and debugging skills.
  • Excellent written and verbal communication skills.
  • Detail-oriented with a passion for data accuracy, security, and reliability.
  • Ability to work independently and collaboratively across teams.

If you are passionate about cloud data solutions, business intelligence, and data-driven decision-making, we encourage you to apply!

Why Work for Us?

  • Benefits Coverage: Comprehensive health, dental, vision, and travel insurance.
  • Health Care Spending Account: Additional financial support for health-related expenses.
  • Pension Plan: Company-supported pension scheme.
  • Incentive Plans: Progressive employee incentive plans.
  • Talent Development: Opportunities for professional growth and development.
  • Company Recreation Club: Participate in fun activities, draws with exciting prizes, summer BBQs, holiday parties, and more!

Amphenol Canada is committed to developing inclusive, barrier-free selection processes and work environments. If contacted in relation to a job opportunity, you should advise Amphenol, in a timely fashion, of the accommodation measures which must be taken to enable you to be assessed in a fair and equitable manner. Information received relating to accommodation measures will be addressed confidentially.

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