Senior Data Engineer
R.S. Hughes Co., Inc.About the role
Imagine a company that recognizes excellence in not only the products it sells, but also in its employees. R.S. Hughes Company, Inc. is that company. We hold ourselves to the highest standards of quality and professionalism — and we treat our employees like the valuable assets they are.
Founded in 1954, R.S. Hughes Co., Inc. is a dynamic, North American distributor of industrial supplies. With 49 warehouse sites in the United States and Mexico, we maintain an extensive inventory of adhesives, abrasives, electrical, static control, tapes, labeling and safety products. We are proud to represent products from leading manufacturing companies including 3M, Henkel Loctite, Momentive, Brady, Kimberly Clark, Ansell Edmont, and many others. We specialize in sales and service solutions to manufacturing companies in both OEM and MRO applications.
In addition to competitive salaries and benefits, we offer an environment that asks you to make a difference. We value hard work and common sense, and we consistently reward those that exemplify these traits. If you're looking for a great team to grow with and if you are willing to embrace the challenges of being expected to be the best, we welcome you to come join the R.S. Hughes Company, Inc. team!
Job Summary
R.S. Hughes is seeking a Senior Data Engineer to support and evolve our enterprise analytics platform. This role is responsible for designing, building, and maintaining scalable data pipelines and analytics-ready data models that power reporting and decision-making across the organization.
The ideal candidate brings strong experience in Azure-based data engineering, dimensional modeling, and enterprise analytics enablement, with a mindset oriented toward data quality, performance, and long-term maintainability.
Core Responsibilities
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Data Ingestion & Integration
- Design, develop, and maintain robust ELT/ETL pipelines using Azure Synapse Analytics, Azure Logic Apps, and related Azure services
- Ingest data from diverse source systems including databases, flat files, and REST and Microsoft Graph APIs
- Develop and maintain custom API integrations using Python and/or PySpark notebooks
- Own end-to-end onboarding of new data sources, from initial extraction through production-ready modeling
Data Transformation & Modeling
- Implement data transformations using SQL stored procedures aligned to a medallion architecture (Bronze, Silver, Gold)
- Apply Kimball dimensional modeling techniques to deliver clean, performant star schemas
- Make thoughtful design decisions around:
- Star vs. snowflake schemas
- Normalized vs. denormalized datasets
- Conformed dimensions across multiple source systems
- Ensure data models are optimized for consumption by Power BI report developers and analysts
Data Quality & Governance
- Validate source data and implement data quality checks throughout the pipeline lifecycle
- Troubleshoot and resolve data issues related to freshness, accuracy, and completeness
- Maintain clear and accurate documentation for pipelines, models, and business logic to support enterprise understanding and reuse
Analytics Enablement
- Deliver curated, semantic-ready datasets that serve as trusted sources for enterprise reporting
- Collaborate closely with BI developers, analysts, and business stakeholders to understand and translate analytica
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