Data Engineer

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.