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Added 1 hour ago
AI
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Amphenol Communications Solutions

Data Engineer

Markham, ON, Canada

The base salary range for this position is $110,000 - $135,000 annually. · Full-time

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Job details

Pay: The base salary range for this position is $110,000 - $135,000 annually.
Job type: Full-time
Apply by: Nov 28, 2026
Experience: 5+ years of hands-on data engineering or relevant software engineering experience, including ownership of production data pipelines and integrations.
Posting language: English
Posted: Oct 29, 2026

Original job description

Location: Markham, ON Posted: 10/29/2026 Location Name: HSIO-Markham

Wage Max: 135,000.00 Annual Wage Min: 110,000.00 Annual Position Type: Full Time

Amphenol Communications Solutions (ACS), a division of Amphenol Corporation, is a world leader in interconnect solutions for Communications, Mobile, RF, Optics, and Commercial electronics markets. Amphenol Corporation is one of the world’s largest designers and manufacturers of electrical, electronic and fiber optic connectors and interconnect systems, antennas, sensors and sensor-based products and coaxial and high-speed specialty cable. ACS has an expansive global presence in research and development, manufacturing, and sales. We design and manufacture a wide range of innovative connectors as well as cable assemblies for diverse applications including server, storage, data center, mobile, RF, networking, industrial, business equipment, and automotive.

Amphenol is one of the largest manufacturers of interconnect products in the world. The Company designs, manufactures and markets electrical, electronic and fiber optic connectors, coaxial and flat-ribbon cable, and interconnect systems. The primary end markets for the Company's products are communications and information processing markets, including cable television, cellular telephone and data communication and information processing systems; aerospace and military electronics; and automotive, rail and other transportation and industrial applications.

Amphenol Communications Solutions (ACS), a division of Amphenol Corporation, is a world leader in interconnect solutions for Communications, Mobile, RF, Optics, and Commercial electronics markets. Amphenol Corporation is one of the world’s largest designers and manufacturers of electrical, electronic and fiber optic connectors and interconnect systems, antennas, sensors and sensor-based products and coaxial and high-speed specialty cable. ACS has an expansive global presence in research and development, manufacturing, and sales. We design and manufacture a wide range of innovative connectors as well as cable assemblies for diverse applications including server, storage, data center, mobile, RF, networking, industrial, business equipment, and automotive.

Amphenol High Speed Products Group is the market leader for high-speed IO products. Our products help to enable the electronics revolution and remain a key enabler for all the major Tier 1 OEMs globally.

Data Engineer

Position: Data Engineer

Location: Markham

Reports To: Director of IT Applications

Position Summary

We are seeking a Data Engineer with strong hands-on engineering and software development capabilities to build, integrate, and operate the enterprise data platform. The role will develop reliable data services connecting global business applications, databases, APIs, and files, and support the transition to future data platforms. Data accuracy, completeness, security, and compliance are central to every stage of delivery.

The engineer will own implementation quality and operational reliability for assigned data platform components, pipelines, and integrations. Strong SQL and Python programming, automated testing, and disciplined software engineering are essential. Working with architecture, databases, security, modeling, and BI teams, the role will implement governed data controls, support platform upgrades and migration, and deliver trusted data for business reporting, manufacturing insights, and future analytics capabilities.

ATTRIBUTES

Strong engineering fundamentals and hands-on development
Structured troubleshooting and root-cause analysis
Ownership of production quality and reliability
Automation, reusable design, and continuous improvement
Clear documentation and effective technical collaboration

Responsibilities

Support and operate the enterprise data platform and integrations, from detailed design and development through testing, migration, production support, and continuous improvement.

ACTIVITY

Description

Data Platform Engineering

Build and maintain enterprise data platform components, ingestion frameworks, storage structures, and reusable transformation services using SQL, Python, Azure Data Factory, and Fabric as applicable. Apply approved architecture patterns, modular design, metadata-driven configuration, and clear interfaces to support growth and maintainability.

Enterprise Integration

Engineer dependable integrations across ERP, MES, CRM, SharePoint, applications, databases, APIs, and files. Implement full and incremental loading, change data capture where supported, schema validation, and dependency management. Coordinate source extraction windows, interface changes, and data contracts with upstream and downstream owners.

Data Accuracy and Integrity

Implement automated validation, reconciliation, deduplication, completeness, freshness, and business-rule checks. Validate source-to-target mappings and transformation logic; quarantine exceptions and track remediation. Handle late, missing, or changed data explicitly and obtain agreed quality acceptance from data owners and downstream consumers.

Platform Upgrades and Migration

Support future platform evaluation, upgrades, and migration through dependency assessment, pipeline refactoring, data transfer, and regression testing. Validate record counts, control totals, transformations, security, and downstream behavior. Execute agreed parallel runs, cutover, rollback or recovery, and post-migration monitoring to protect business continuity.

Software Engineering and Automation

Develop maintainable SQL and Python code with version control, peer review, and meaningful automated tests. Build controlled CI/CD with environment-specific configuration and secure secrets handling. Automate deployment and repeatable operations, and document changes, release procedures, and recovery of affected data.

Reliability and Performance

Monitor availability, throughput, latency, freshness, capacity, and cost. Optimize queries and processing; implement actionable logs, alerts, checkpoints, bounded retries, and idempotent recovery. Manage restart, replay, and backfill procedures to prevent missing or duplicate records. Resolve incidents and eliminate recurring failures.

Security Compliance and Governance

Implement approved least-privilege access, secure identities, encryption, classification, retention, and sensitive-data protection across assigned workloads. Maintain lineage, mappings, change records, and audit evidence. Remediate identified control gaps with Security and Compliance; escalate exceptions for approval and provide runbooks, knowledge transfer, and backup coverage.

Qualifications

Bachelor’s degree in computer science, Software Engineering, Information Systems, Engineering, or a related field, or equivalent relevant experience.
5+ years of hands-on data engineering or relevant software engineering experience, including ownership of production data pipelines and integrations.
Advanced SQL and strong Python programming skills, including complex transformations, efficient data processing, modular code, error handling, and automated testing.
Strong practical Azure Data Factory and cloud data platform engineering experience, with the ability to support platform upgrades, workload migration, regression testing, cutover, and recovery planning. Microsoft Fabric experience is preferred.
Proven experience with ETL and ELT, orchestration, incremental loading, change data capture, API integration, data reconciliation, and schema evolution.
Ability to design reliable processing with idempotency, retries, checkpoints, controlled backfills, and recovery from partial failures; able to explain implementation tradeoffs and production incidents resolved.
Experience with Git, code review, CI/CD, automated testing, monitoring, and secure credential handling; practical ability to implement data access, protection, retention, and audit controls under enterprise policies.
Strong understanding of relational databases, data lake storage, file formats, dimensional modeling fundamentals, and performance optimization.
Ability to translate requirements into technical designs, diagnose issues across systems, document solutions, and collaborate effectively with global business and technical teams.

Preferred Experience

Microsoft Fabric Data Factory, Lakehouse, Warehouse, OneLake, and Delta tables; manufacturing and ERP or MES integrations, including QAD, Plex; event-driven ingestion or streaming where required; infrastructure as code; and enterprise data governance practices.

Come join the Amphenol family!

The base salary range for this position is $110,000 - $135,000 annually. In determining the rate of pay, Amphenol considers a variety of nondiscriminatory factors, including but not limited to geographic location, relevant industry experience, qualifications, skills, and education. It would be rare for an individual to be hired at or near the top of the range for a given role. Base salary is one facet of Amphenol's total rewards package which includes participation in our comprehensive benefits program with medical, dental, and vision benefits, vacation, sick leave, paid holidays, life insurance, short/long term disability, and membership in our Defined Contribution Pension Plan.

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.

Amphenol Corporation is proud of our reputation as an excellent employer. Our focus is to provide the highest level of support and responsiveness to both our employees and our customers, the world's largest technology companies. Amphenol Corporation offers the opportunity for career growth within a global organization. We believe that Amphenol Corporation is unique in that every employee, regardless of his or her position, has the ability to positively impact the business.

Amphenol is an “Equal Opportunity Employer” - Minority/Female/Disabled/Veteran/Sexual Orientation/Gender Identity/National Origin. For additional company information please visit our website at https://www.amphenol-cs.com/

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More about this job

Responsibilities

Build, integrate, and operate enterprise data platform components and reliable pipelines connecting business applications, databases, APIs, and files. Ensure data quality, security, performance, and production reliability while supporting platform upgrades, migrations, monitoring, and continuous improvement.

Requirements

Requires a bachelor’s degree in a relevant field or equivalent experience, plus at least five years of hands-on data or software engineering experience owning production pipelines and integrations. Candidates need advanced SQL, strong Python, practical Azure Data Factory and cloud platform experience, and expertise in testing, orchestration, data quality, security, and production recovery; Microsoft Fabric experience is preferred.

Skills

SQL
Python
Azure Data Factory
Microsoft Fabric
ETL And ELT
Data Pipeline Engineering
API Integration
Data Validation
Automated Testing
CI/CD
Git
Data Migration
Change Data Capture
Data Modeling
Cloud Data Platforms
Data Governance

Benefits

Medical Benefits
Dental Benefits
Vision Benefits
Vacation
Sick Leave
Paid Holidays
Life Insurance
Short-Term Disability
Long-Term Disability

Visa sponsorship

Not detected in the job text

Keywords

SQL
Python
Azure Data Factory
Microsoft Fabric
Data Engineering
Enterprise Data Platform
ETL
ELT
Data Pipelines
Data Integration
API Integration
Change Data Capture
Incremental Loading
Data Validation
Data Reconciliation
Schema Evolution
CI/CD
Git
Automated Testing
Data Migration
Lakehouse
Data Warehouse
OneLake
Delta Tables
Dimensional Modeling
Data Governance
Data Security
ERP
MES
QAD

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