> Markdown version of [/jobs/ext/4518283-data-engineer](https://www.wearedevelopers.com/jobs/ext/4518283-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Robotics Technologies LLC - **Location:** Columbia, MO, United States - **Contract:** Temporary contract - **Skills:** Business Analytics Applications, Data Analysis, Microsoft Azure, Big Data, Extract Transform Load (ETL), Data Visualization, Relational Databases, Python (Programming Language), Performance Tuning, Power BI, SQL Databases, Systems Integration, Data Processing, Data Ingestion, Azure Data Factory, Data Pipelines, Databricks - **Published:** November 1, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=88a95129bb906d46 ## About the Role * Hands-on experience with Microsoft Azure (Data Factory, Synapse, Storage, etc.). * Proficiency in Databricks for big data processing and analytics. * Strong Python programming skills for data manipulation, automation, and integration. * Expertise in Power BI for dashboard creation and data visualization. * Solid understanding of SQL and relational database concepts. * Experience with data modeling and performance tuning. * Excellent communication skills to work effectively with technical and non-technical stakeholders. ## Description We are seeking an experienced Azure Data Engineer with strong expertise in Azure Data Factory (ADF), Databricks, Python, SQL, and Power BI to design, develop, and optimize scalable data pipelines and analytics solutions., * Design and develop data pipelines using Azure Data Factory, Databricks, and other cloud-native tools. * Implement ETL processes to ensure efficient data ingestion, transformation, and storage. * Collaborate with business stakeholders to understand reporting needs and deliver actionable insights. * Develop and maintain dashboards in Power BI to support decision-making across teams. * Optimize data workflows for performance, scalability, and reliability. * Ensure data quality and governance standards are met across all systems. * Troubleshoot and resolve issues related to data pipelines, integrations, and reporting.