Datasets Jobs in Michigan (NOW HIRING)

The Data Engineer is responsible for developing, maintaining, and optimizing the organization's data platform, with a primary focus on transforming raw data into structured, report-ready datasets. This role works extensively with data sourced from Microsoft Dynamics 365 via Synapse Link, transforming Bronze data into curated Silver datasets within the organization's data lake to support reporting, analytics, and business decision-making.

The Data Engineer is also responsible for automating data pipelines, enabling report delivery, and assisting in the creation of reports and dashboards within the Microsoft ecosystem, including Power BI, Azure, and Synapse. This role partners closely with business stakeholders to translate reporting requirements into technical data solutions.

• Design, build, and maintain data pipelines to transform raw Bronze data into curated Silver datasets.
• Develop and maintain data structures within the data lake to support reporting and analytics.
• Work with data sourced from Microsoft Dynamics 365 via Synapse Link and other internal systems.
• Create and maintain data models using joins, transformations, and normalization to improve usability and performance.
• Ensure data quality, consistency, and integrity across datasets.
• Validate Gold data against source systems.
• Maintain and optimize the performance of data transformations and queries.
• Support integration between data sources, reporting tools, and downstream systems.
• Assist in defining and evolving data architecture standards (Bronze Silver Gold).
• Build and maintain datasets used for reporting and analytics.
• Create and enhance Power BI dashboards and reports based on business needs.
• Work with stakeholders to define reporting requirements and translate them into technical solutions.
• Optimize data for efficient reporting and visualization performance.
• Automate data refreshes, report delivery, and scheduled processes.
• Build workflows and automation for data movement and reporting pipelines.
• Support integration and automation within the Microsoft ecosystem, including Azure services and Power Platform.
• Work directly with business stakeholders across Finance, Operations, Supply Chain, and other departments to understand reporting needs.
• Translate business requirements into data models and reporting solutions.
• Support ad hoc data requests and analysis.
• Provide guidance on best practices for data usage and reporting.
• Document data pipelines, transformations, and architecture.
• Ensure data governance practices are followed, including naming standards and documentation.
• Maintain visibility into how data flows from source systems to reports.

• 3+ years of experience in data engineering, data analytics, or a related role.
• Experience working with Azure data platforms (such as Data Lake, Synapse, or similar).
• Strong SQL skills and experience working with relational data.
• Experience building data transformations and working with structured and unstructured datasets.
• Experience supporting reporting and analytics workflows.
• Strong understanding of data modeling and data pipeline concepts.
• Strong problem-solving and analytical skills.
• Experience working with Microsoft Dynamics 365 data (Synapse Link, Dataverse, etc.).
• Experience with Power BI, including dashboard creation, data modeling, and DAX.
• Experience with the medallion architecture (Bronze / Silver / Gold).
• Familiarity with Azure services such as Data Factory, Synapse, or Power Platform.
• Experience with data integration across multiple systems (ERP, eCommerce, etc.).
• Exposure to Databricks or similar tools (not required).
• Ability to operate in a fast-paced environment with shifting priorities.
• Strong collaboration skills across business and technical teams.
• Self-driven with the ability to own data pipelines and reporting solutions end-to-end.
• Detail-oriented with a focus on data accuracy and consistency.
• Strong communication skills with the ability to explain complex data concepts in simple terms.

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