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# Staff Analytics Engineer

- **Company:** GE Vernova
- **Location:** United States
- **Experience:** Expert
- **Salary:** $123,200.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, BigQuery, Continuous Integration, Information Engineering, Data Infrastructure, Data Systems, Distributed Computing Environment, Supervisory Control and Data Acquisition (SCADA), Python (Programming Language), Scrum Methodology, Release Management, Power BI, Cloud Services, Software Engineering, SQL Databases, Tableau (Software), Snowflake, Apache Spark, Data Layers, Information Technology, Data Analytics, Plotly, Streamlit Framework, Software Version Control, Data Pipelines, Amazon Redshift, Databricks
- **Published:** October 29, 2026
- **Apply:** https://jobs.military.com/career/380979/sr-staff-analytics-engineer-south-carolina-sc-greenville

## About the Role

You are a technically strong analytics engineer who is equally comfortable working in the data layer and collaborating with domain experts. You bring production discipline to your craft and the communication skills to operate effectively across engineering, product, and business stakeholders.\n, * A formal education and subsequent Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Analytics, Mathematics, Statistics, or a related STEM field is nice to have, but we are most interested in your total experience and professional achievements.\n

 * 8+ years of professional experience in analytics engineering, data engineering, software engineering, or a closely related technical field.\n
 * Strong hands-on experience with Python and SQL for building production-quality analytics and data solutions.\n
 * Experience designing, building, and supporting data pipelines, data models, and analytics workflows in industrial, engineering, or enterprise environments.\n
 * Experience developing dashboards and data applications using Power BI, Tableau, Plotly Dash, Streamlit, or similar tools.\n
 * Experience applying CI/CD, version control, testing, and release management practices in data and analytics environments.\n
 * Experience working in Agile/Scrum delivery teams, including backlog management, sprint planning, and cross-functional coordination.\n, * Experience working with wind turbine, SCADA, sensor, operational, or event data in an analytics or engineering context.\n
 * Hands-on experience with modern data platforms such as Databricks, Spark, Snowflake, Redshift, BigQuery, or equivalent distributed processing tools.\n
 * Familiarity with cloud data platforms and platform-oriented engineering approaches for scalable analytics delivery.\n