
Data Engineer
- Detroit, MI
- Permanent
- Full-time
- 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
- 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