Data Engineer

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.

The Data Engineer will support the Information Systems Lead by building and maintaining the data pipelines, integrations, lakehouse structures, and curated data products required for scalable analytics, automation, and AI readiness across CBS. This role is responsible for turning fragmented business data from source systems into reliable, governed, and reusable datasets. The Data Engineer will work closely with the IS Lead, Data Analyst, Business Analyst, corporate IT, implementation partners, functional data owners, and the AI Solutions & Automation team.

The role is focused on source-system onboarding, ETL/ELT pipelines, data quality, orchestration, medallion architecture, and production data reliability. AI solution design and business workflow automation will be owned by the AI Solutions & Automation team, with the Data Engineer providing the trusted data foundation required to support those solutions.

• Design, build, test, and maintain scalable data pipelines from priority source systems into the CBS cloud/lakehouse environment.
• Integrate data from enterprise and functional systems including ERP, MES, PLM, QMS, SI/test data, SharePoint/file repositories, Azure SQL, and other business platforms.
• Implement ETL/ELT patterns, data transformations, and medallion architecture layers including raw, cleaned, curated, and business-ready datasets.
• Develop data quality checks, validation logic, reconciliation methods, exception handling, and monitoring to ensure trusted and reliable data products.
• Support secure on-prem-to-cloud data integration patterns including database/API connectivity, file-based ingestion, scheduled refreshes, and batch or event-based processing.
• Partner with the IS Lead to develop data models, semantic layers, standardized KPIs, and reusable data assets that support dashboards, analytics, automation, and AI use cases.
• Partner with the Data Analyst and Business Analyst to understand reporting requirements, business definitions, and functional data needs.
• Support the AI Solutions & Automation team by preparing AI-ready datasets, defining data access patterns, and ensuring data products are governed, reliable, and reusable.
• Build and maintain orchestration, scheduling, logging, alerting, and pipeline documentation to support production operations and sustainment.
• Collaborate with corporate IT, security teams, and data owners to implement access controls, data lineage, naming standards, environment controls, and data governance requirements.
• Support implementation partners and vendors during architecture, pipeline build, source-system integration, testing, documentation, and handoff activities.
• Troubleshoot data issues, performance problems, refresh failures, and source-system changes that affect downstream analytics or automation capabilities.
• Contribute to continuous improvement of data engineering standards, development practices, documentation, and reusable pipeline patterns.
• Travel as required to support global operations and source-system discovery or deployment activities.
• Perform other duties and responsibilities as required to support the growth and success of the business.

• BS in Computer Science, Information Systems, Data Engineering, Data Analytics, Engineering, or related field.
• 3-7+ years of experience in data engineering, analytics engineering, ETL/ELT development,…