<p>The Senior Data Engineer plays a key role in architecting, developing, and operating reliable, production-ready data solutions that enable analytics, automation, and operational processes across our client’s organization.</p><p><br></p><p>Operating within a modern, cloud-based data ecosystem, this role is responsible for bringing together data from internal platforms and external partners, transforming it into trusted, high-quality assets, and delivering it consistently to downstream users and systems. The work spans the full data lifecycle—ingestion, orchestration, transformation, and delivery—and blends advanced SQL development with Python-based pipeline and workflow automation.</p><p><br></p><p>This role sits at the intersection of data and systems engineering and works closely with Business Intelligence, Business Technology, and operational teams to ensure data solutions are scalable, dependable, and aligned with real business outcomes.</p><p><br></p><p><br></p><p><br></p><p><br></p>
We are looking for a talented Data Engineer to join our team in Grand Rapids, Michigan. In this role, you will focus on designing, building, and optimizing robust data solutions using Snowflake and other cloud-based technologies. You will work closely with business intelligence and analytics teams to deliver scalable, high-performance data pipelines that support organizational goals.<br><br>Responsibilities:<br>• Design and implement scalable data models, schemas, and tables within Snowflake, including staging, integration, and presentation layers.<br>• Develop and optimize data pipelines using Snowflake tools such as Snowpipe, Streams, Tasks, and stored procedures.<br>• Ensure data security and access through role-based controls and best practices for data sharing.<br>• Build and maintain ETL pipelines leveraging tools like dbt, Matillion, Fivetran, Informatica, or Azure-native solutions.<br>• Integrate data from diverse sources such as APIs, IoT devices, and NoSQL databases to create unified datasets.<br>• Enhance performance by utilizing clustering, partitioning, caching, and efficient warehouse sizing strategies.<br>• Collaborate with cloud technologies such as AWS, Azure, or Google Cloud to support Snowflake infrastructure and operations.<br>• Implement automated workflows and CI/CD processes for seamless deployment of data solutions.<br>• Maintain high standards for data accuracy, completeness, and reliability while supporting governance and documentation.<br>• Work closely with analytics, reporting, and business teams to troubleshoot issues and deliver scalable solutions.