Data Engineer

Title: Data Engineer

Location: Nashua NH

The Data Engineer will support the Information Systems Lead by building andmaintaining the data pipelines, integrations, lakehouse structures, and curateddata products required for scalable analytics, automation, and AI readinessacross CBS. This role is responsible for turning fragmented business data fromsource systems into reliable, governed, and reusable datasets.

The Data Engineer will work closely with the IS Lead, Data Analyst, BusinessAnalyst, corporate IT, implementation partners, functional data owners, and theAI Solutions & Automation team. The role is focused on source-system onboarding,ETL/ELT pipelines, data quality, orchestration, medallion architecture, andproduction data reliability. AI solution design and business workflow automationwill be owned by the AI Solutions & Automation team, with the Data Engineerproviding the trusted data foundation required to support those solutions.

RESPONSIBILITIES:

Design, build, test, and maintain scalable data pipelines from prioritysource 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 otherbusiness platforms.Implement ETL/ELT patterns, data transformations, and medallion architecturelayers 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 includingdatabase/API connectivity, file-based ingestion, scheduled refreshes, and batchor 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 reportingrequirements, 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, andpipeline documentation to support production operations and sustainment.Collaborate with corporate IT, security teams, and data owners to implementaccess controls, data lineage, naming standards, environment controls, and datagovernance requirements.Support implementation partners and vendors during architecture, pipelinebuild, source-system integration, testing, documentation, and handoffactivities.Troubleshoot data issues, performance problems, refresh failures, andsource-system changes that affect downstream analytics or automationcapabilities.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 discoveryor deployment activities.Perform other duties and responsibilities as required to support the growthand success of the business.

QUALIFICATIONS:

BS in Computer Science, Information Systems, Data Engineering, DataAnalytics, Engineering, or related field.3-7+ years of experience in data engineering, analytics engineering, ETL/ELTdevelopment, data integration, or cloud data platform implementation.Strong SQL skills and experience building data models, transformations,joins, validations, and production-ready datasets.Experience with Python, PySpark, notebooks, or comparable data engineeringtools strongly preferred.Experience with modern cloud data platforms such as Microsoft Fabric, AzureData Lake, Azure Data Factory, Synapse, Databricks, Snowflake, or comparableplatforms.Familiarity with lakehouse architecture, medallion data structures, semanticmodels, data quality controls, pipeline orchestration, and data governanceconcepts.Experience integrating data from ERP, MES, PLM, QMS, manufacturing,engineering, or operational systems strongly preferred.Experience with APIs, file ingestion, database extraction, scheduledrefreshes, and on-prem-to-cloud data movement preferred.Familiarity with Power BI, semantic models, DAX, or business intelligenceconsumption patterns preferred.Experience with Git, DevOps practices, deployment management, testing,monitoring, and documentation preferred.Strong analytical, troubleshooting, communication, and problem-solvingskills.Ability to work with business stakeholders, technical teams, and externalpartners to translate source-system data into reliable business-ready assets.Travel required as needed to support global sites and data integrationactivities.