2026012 - Senior Software Analyst

John Deere John Deere · Industrial · Chicago, IL +1 · Technology (CA)

This role focuses on designing, architecting, and maintaining scalable cloud-based data solutions, including data pipelines, lakehouses, and semantic models. It involves developing agentic workflows and automation solutions, creating Power BI reports, and managing cloud data infrastructure with CI/CD practices. The role also requires developing and applying statistical models and ensuring data governance and compliance.

What you'd actually do

  1. Design, architect, and maintain scalable cloud based data solutions while building and optimizing data pipelines, lakehouses, and semantic models.
  2. Develop agentic workflows and automation solutions to improve efficiency and reliability and create interactive Power BI reports to enable data driven decision making.
  3. Manage and evolve cloud data infrastructure, implement CI/CD practices for data engineering, and collaborate closely with cross functional teams while providing technical leadership within Agile environments.
  4. 25% domestic travel required to meet development teams and visit dealers.

Skills

Required

  • design, develop, and optimize scalable cloud based data architectures across Azure, AWS, and GCP
  • SQL
  • Pyspark
  • Python
  • Microsoft Fabric
  • Apache Spark
  • Databricks
  • Power BI
  • Tableau
  • CI/CD pipelines
  • DevOps tools (e.g., GitHub Actions, Azure DevOps)
  • ServiceNow integrations
  • Enterprise Data Lake platform
  • AWS cloud services
  • Azure cloud services
  • statistical models
  • regression analysis
  • forecasting techniques
  • python statistical/ ML libraries
  • data governance frameworks
  • data quality controls
  • enterprise and regulatory standards
  • Microsoft Purview

Nice to have

  • agentic workflows
  • automation solutions

What the JD emphasized

  • 5 years of experience in design, develop, and optimize scalable cloud based data architectures across Azure, AWS, and GCP, leveraging SQL, Pyspark, Python to build performant, reliable, and maintainable data pipelines
  • 5 years of experience in build and optimize data pipelines and lakehouses using Microsoft Fabric, Apache Spark, and Databricks
  • 5 years of experience in create dashboards and reports using Power BI and Tableau
  • 3 years of experience in implement CI/CD pipelines and monitor data product health using DevOps tools (e.g., GitHub Actions, Azure DevOps)
  • 4 years of experience in develop and customize ServiceNow integrations and automate workflows
  • 5 years of experience in perform data integration across enterprise systems using Enterprise Data Lake platform, Databricks, AWS and Azure cloud services, Microsoft Fabric
  • 5 years of experience in develop and apply statistical models, regression analysis, and forecasting techniques to business data to evaluate performance, identify anomalies, and support strategic planning using python statistical/ ML libraries
  • 5 years of experience in partner with business, security, legal, and analytics teams to establish data governance frameworks, implement data quality controls, and ensure compliance with enterprise and regulatory standards using tool like Microsoft Purview, Deere Enterprise data lake, Databricks

Other signals

  • design, architect, and maintain scalable cloud based data solutions
  • building and optimizing data pipelines, lakehouses, and semantic models
  • develop agentic workflows and automation solutions
  • develop and apply statistical models, regression analysis, and forecasting techniques