Data Engineer

Konica Minolta Business Solutions U.S.A., Inc. is looking for a Data Engineer to join their Data Science & Analytics team. The role involves designing and maintaining enterprise-scale data warehouse solutions, optimizing data pipelines, and ensuring data quality to support business insights.

Responsibilities:

• Design and implement and maintain enterprise-scale data warehouse solutions using dimensional modeling best practices (Kimball methodology, Star Schema)
• Ingest and stage data following pre-defined patterns and methods
• Architect and optimize data pipelines using modern ETL/ELT tools including Azure Data Factory, SSIS, or Python/C#
• Support organization data products and analytics needs
• Implement data quality frameworks and monitoring to ensure data integrity and trustworthiness
• Build and launch new data models and data pipelines in production
• Maintain clear, up-to-date documentation for deployed models, pipelines, architecture, and workflows
• Leverage source control and DevOps processes to standardize workflows and automation

Requirements:

• Undergraduate degree in Computer Science, Math, Physics, or related technical fields
• 4+ years of professional experience as data architect, data engineer, data scientist, etc
• Hands-on experience building secure and reliable data architecture on Microsoft SQL Server, particularly with SSIS, Python and/or C#
• Experience working with scalable data systems that leverage a hybrid approach of batch processing and real-time data streaming
• Experience working in source control and DevOps/DataOps environments
• Experience in data warehousing and data modeling, data architecture, ETL/ELT processes, version control and DevOps practices like CI/CD pipelines and infrastructure-as-code tools
• Understanding of how to maintain ETLs operating on a variety of structured and unstructured sources
• C#, Python, Azure Data Factory and SQL skills for data manipulation, scripting and automating workflows
• Strong critical thinking and problem-solving skills
• Strong communication skills for technical and non-technical audiences
• Experience working in an agile/scrum delivery model
• Understanding of open-source tooling and their applications within the data ecosystem
• Experience working with a CLI and scripting for efficient system administration
• Experience implementing monitoring, alerting, and logging mechanisms for proactive system health checks