Senior Data Engineer

R.S. Hughes Co, Inc

Salt Lake City (UT)

On-site

USD 106,000 - 130,000

Full time

4 days ago
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Benefits offered by this job

Life insurance
Short-term disability
401(k)

Job summary

R.S. Hughes Company, Inc. seeks a Senior Data Engineer to design, build, and maintain scalable data pipelines and analytics-ready data models powering reporting and decision-making across the organization.

Ideal candidates bring strong experience in Azure-based data engineering, dimensional modeling, and enterprise analytics enablement, with a focus on data quality, performance, and maintainability.

Qualifications

  • 3+ years of experience in Data Engineering or Analytics Engineering roles.
  • Strong hands-on experience with Azure Synapse Analytics and Azure SQL Database.
  • Proven experience designing and orchestrating ELT/ETL pipelines.
  • Experience integrating SaaS platforms using REST APIs.
  • Advanced proficiency in SQL, including complex transformations and stored procedures.
  • Experience using Python and/or PySpark for data extraction and transformation.
  • Experience designing and maintaining incremental data processing patterns to scale.
  • Deep understanding of medallion architecture principles.
  • Strong knowledge of dimensional modeling (Kimball).
  • Experience delivering star schemas for analytical workloads.

Responsibilities

  • Design, build, and maintain scalable data pipelines and analytics-ready data models.
  • Ingest data from diverse sources and onboard new data sources end-to-end.
  • Transform data using medallion architecture and Kimball techniques.
  • Ensure data quality, governance, and documentation for pipelines and models.
  • Collaborate with BI developers and analysts to enable reporting.
  • Support and maintain Power BI star schemas and enterprise analytics.

Skills

Azure Synapse Analytics
Azure SQL Database
ELT/ETL pipelines
Python
PySpark
SQL
Dimensional modeling (Kimball)
Power BI
REST APIs
Data quality & governance
Data ingestion & integration

Education

Bachelor's degree in Computer Science / Engineering

Tools

Azure Synapse Analytics
Azure SQL Database
PySpark

Job description

life insurance, short term disability, 401(k)

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
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
  • 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 analytical requirements
  • Support and maintain existing Power BI star schemas used across the organization
Basic Qualifications
  • 3+ years of experience in Data Engineering or Analytics Engineering roles
  • Strong hands-on experience with Azure Synapse Analytics and Azure SQL Database (or closely related technologies)
  • Proven experience designing and orchestrating ELT/ETL pipelines
  • Experience integrating SaaS platforms using REST APIs
  • Advanced proficiency in SQL, including complex transformations and stored procedures
  • Experience using Python and/or PySpark for data extraction and transformation
  • Experience designing and maintaining incremental data processing patterns to efficiently ingest and transform data at scale
  • Deep understanding of medallion architecture principles
  • Strong applied knowledge of dimensional modeling (Kimball)
  • Demonstrated ability to design performant star schemas for analytical workloads
  • Comfort performing light DBA responsibilities in Azure SQL Database, including:
  • Monitoring storage usage, compute utilization, and performance
  • Managing cost awareness and optimization
  • Supporting schema changes, deployments, and operational stability
Skills
  • Familiarity with data quality frameworks or validation tooling
  • Experience working in large-scale, enterprise reporting environments
  • Strong documentation and written communication skills
  • Exposure to modern analytics governance or semantic modeling concepts
  • Experience supporting enterprise analytics in Power BI
  • Experience mentoring, coaching, or training others in data engineering or analytics best practices
Certifications & Licenses
  • Advanced certifications in data management, Microsoft SQL Server, or Progress databases preferred.
Compensation

Our merit-based salary/bonus program offers exceptional growth opportunities. We provide a comprehensive medical, dental, life insurance, wellness benefit, short term disability plan, paid vacation, and a 401(k) retirement savings plan, and an Employee Stock Ownership Program (ESOP), where employees are eligible after 30 days of service.

Compensation for this exempt role is up to $118,000 DOE.

Qualifications Education Bachelors of Computer Science (required) Bachelors of Computer Engineering (required) Experience 3 years: Data Engineering, Analytics Engineering (required)

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

This employer is required to notify all applicants of their rights pursuant to federal employment laws.

For further information, please review the Know Your Rights notice from the Department of Labor.

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