Grainger

Data Engineer

Grainger

full-time

Posted on:

Origin:  • 🇺🇸 United States • Wisconsin

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Job Level

Mid-LevelSenior

Tech Stack

Amazon RedshiftAWSAzureBigQueryCloudETLMS SQL ServerMySQLPostgresPythonSQLTableau

About the role

  • Recommend and implement data architecture and accessibility strategies to ensure scalability, reliability, and value creation.
  • Collaborate with stakeholders to align enterprise and data architectures, maximizing the value of organizational data.
  • Create and maintain logical data models and physical database designs for analytics ecosystems.
  • Design and develop data warehouses and implement ETL (Extract, Transform, Load) processes.
  • Build and maintain business intelligence (BI) solutions to support enterprise-wide decision-making.
  • Establish and execute system performance assessments, recommending infrastructure improvements as needed.
  • Develop standards, process flows, and tools for mapping data sources, documenting interfaces, and tracking data movement.
  • Define governance practices and metadata standards to ensure accuracy, consistency, and reusability of enterprise data.
  • Support integration of machine learning and big data technologies into infrastructure to drive innovation.

Requirements

  • Bachelor’s degree in Computer Science, Management Information Systems, or a related field
  • 3+ years of experience in data architecture or 5+ years in equivalent data-related roles
  • Proficiency with ETL tools and frameworks
  • Strong SQL skills; experience with R and Python for data transformation and analysis
  • Experience with relational databases such as MySQL and PostgreSQL
  • Knowledge of BI tools such as Power BI, Tableau, or equivalent
  • Excellent problem-solving, communication, and collaboration skills
  • Preferred: Certifications such as ABDE, AWS Certified Data Analytics, Google Professional Data Engineer, Microsoft Azure Data Engineer Associate
  • Preferred: 5+ years as a data engineer with expertise in MS SQL Server, Snowflake, AWS RedShift, and Google BigQuery
  • Preferred: Experience integrating machine learning toolkits into data infrastructure
  • Preferred: Familiarity with big data technologies
  • Preferred: Strong understanding of data modeling, data taxonomy, and data governance practices