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Business Intelligence Data Warehouse Consultant

Remote · USA Full-time New today

Business Intelligence Data Engineering Specialist 3–6 Month Contract (Temp-to-Hire) – Phoenix, AZ Position Overview Join a forward-thinking manufacturing leader in Phoenix as our Business Intelligence Data Engineering Specialist. In this role, you’ll partner closely with operations, finance, and supply chain teams to translate complex business requirements into a scalable, high-performance data architecture. You’ll drive end-to-end BI and data engineering initiatives that empower decision-makers to optimize production, improve quality, and fuel growth.

Key Responsibilities

  • Collaborate with stakeholders to gather and document detailed business requirements across manufacturing functions
  • Design, build, and maintain robust data pipelines and ETL processes for high-volume production, quality, and inventory data
  • Architect and implement scalable data models and data warehouses that support self-service analytics
  • Develop and optimize data integration solutions using SSIS, Azure Data Factory, or equivalent tools
  • Build interactive dashboards and reports with Power BI, Tableau, or similar platforms
  • Ensure data accuracy, consistency, and security through automated validation and monitoring frameworks
  • Troubleshoot performance issues in SQL queries, data jobs, and reporting layers
  • Mentor junior engineers and collaborate with cross-functional teams to implement best practices

Required Qualifications

  • 5+ years of hands-on experience in data engineering, BI development, or data warehousing
  • Proven track record of gathering complex business requirements and translating them into technical solutions
  • Deep expertise in relational databases (SQL Server, Oracle, Teradata) and writing optimized T-SQL or PL/SQL
  • Solid background in ETL tools (SSIS, Azure Data Factory, Informatica, Talend)
  • Hands-on experience building BI solutions with Power BI, Tableau, or QlikView
  • Strong scripting skills in Python, Scala, or shell scripting for data transformations
  • Familiarity with data modeling concepts: star schema, snowflake schema, and normalized designs
  • Excellent communication skills and ability to work in an agile, collaborative environment

Preferred Qualifications

  • Experience in a manufacturing environment, with exposure to MES/ERP systems (SAP, Oracle EBS, or similar)
  • Knowledge of big data technologies: Spark, Hadoop, Kafka, or streaming architectures
  • Cloud data engineering experience on Azure (Synapse, Data Lake Storage) or AWS (Redshift, Glue, S3)
  • Hands-on with automation and CI/CD pipelines for data deployments (Azure DevOps, GitHub Actions)
  • Understanding of Industry 4.0 data flows, IoT device telemetry, and time-series data management
  • Certification in relevant platforms (Microsoft Certified: Azure Data Engineer, AWS Certified Big Data)

Technology Stack Data Integration & ETL

  • SQL Server Integration Services (SSIS)
  • Azure Data Factory / AWS Glue
  • Informatica PowerCenter / Talend

Data Warehousing & Modeling

  • SQL Server / Azure Synapse Analytics
  • Oracle / Teradata
  • Snowflake / Amazon Redshift

Reporting & Visualization

  • Power BI / Tableau
  • SSRS / QlikView

Big Data & Cloud

  • Spark / Hadoop
  • Kafka / AWS Kinesis
  • Azure Data Lake / Amazon S3

Programming & Scripting

  • Python / Scala
  • T-SQL / PL/SQL
  • Shell scripting (Bash, PowerShell)

DevOps & Automation

  • Azure DevOps / GitHub Actions
  • Terraform / ARM templates

What We Offer

  • Opportunity to transition to a full-time role with a leading manufacturer
  • Competitive hourly rate and potential for contract extension
  • Collaborative environment with clear paths for professional growth
  • Hands-on exposure to cutting-edge cloud and big data technologies
  • Supportive team culture that values innovation and continuous improvement

Ready to architect the next generation of data solutions for manufacturing excellence? Apply now and drive real-world impact from day one! Apply Job! Apply to this Job

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