Data Engineer - Manufacturing at Barry-Wehmiller

About Us

Barry-Wehmiller is a globally diversified supplier specializing in engineering consulting and manufacturing technology for packaging, corrugating, sheeting, and paper-converting industries. By combining people-centric leadership with disciplined operational strategies, Barry-Wehmiller has grown into a $3 billion organization with nearly 12,000 team members dedicated to using the power of business to build a better world.

Job Description

MUST HAVE EXPERIENCE IN DATA ENGINEERING AND MANUFACTURING TO BE CONSIDERED FOR THIS OPPORTUNITY

The Manufacturing Data Engineer leads and implements data engineering projects, maintains data pipelines, and provides data estate expertise and best practices company-wide. Previous experience in complex manufacturing data environments is highly preferred.

This role focuses on the development of a modern data platform, encompassing source ERPs & CRMs, Enterprise Data Hub (Lake & Warehouse), Data Governance & Master Data Management, and certified datasets for Reporting & Analytics. The Manufacturing Data Engineer collaborates closely with both business and IT teams to design, build, and support data warehouses and processes vital for business reporting and analytics.

Technologies

Proficient in:

• Azure Synapse Analytics
• Azure Databricks
• Azure Data Factory
• Azure SQL Database
• ADLS
• Entra (Active Directory)
• Key Vault
• Power BI
• Dynamics 365 Finance & Operations
• Dynamics 365 Customer Engagement
• Power Platform
• Dataverse
• Data Governance & MDM solutions
• CDC services
• PySpark notebooks
• Infor XA/SAP ERPs

Principal Duties and Responsibilities

• Assemble and analyze large, complex data sets
• Design and build sustainable database models
• Implement internal process improvements for scalability, data delivery optimization, and automation
• Build infrastructure for data extraction, transformation, and loading using Microsoft Azure, Databricks, and SQL technologies
• Create analytical tools to derive actionable insights on business performance metrics
• Collaborate with stakeholders to solve data-related technical issues
• Establish standards, documentation, and environmental controls
• Mentor team members in ETL and BI solutions design and development
• Contribute to testing, QA, and documentation of data pipelines and systems
• Support data analysis, statistical analysis, predictive analytics, and machine learning models
• Ensure systems comply with industry standards, security, privacy, and data retention requirements
• Participate in and lead Agile/Scrum meetings

Job Specifications

• In-depth understanding of data engineering best practices
• Ability to manage Azure components for ETL/ELT processes
• Experience with coding and scripting tools such as Spark or Pandas
• Expertise in SQL, database administration, and data-related programming elements like Python
• Knowledgeable in database design and complex data models
• Strong facilitation skills for gathering and understanding business requirements
• Ability to develop and maintain strong working relationships
• Management of best practice data backup
• Effective communication skills for non-technical language engagement
• Capacity to manage multiple concurrent projects with tight deadlines
• Proficiency in debugging and diagnosing issues
• Design and implement data solutions to business problems
• Initiative for problem-solving and ownership
• Provide constructive feedback and guidance to other engineers
• Adapt feedback from technical leads

Required Education and Experience

• 3-5 years of experience in data and data analytics development within the Azure cloud platform; Synapse experience preferred
• Experience