Back
Senior, niche industrial-data role lowers competition despite strong GE Vernova brand.
Requires industrial asset, SCADA, and reliability expertise, limiting cross-industry transferability.
Explicit 8+ years and mandatory industrial data, SQL/Python, ETL, and data-quality requirements increase selectivity.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and maintain scalable data pipelines integrating telemetry, alarms, maintenance, and engineering data for GE Vernova's global Solar and Storage fleet.
Develop and enforce fleet asset models, data-quality standards, and traceability controls to enable reliable Root Cause Analysis, performance monitoring, and predictive analytics.
Partner cross-functionally with engineering, reliability, AI, and operations teams to convert fragmented fleet data into reusable, governed engineering intelligence data products.
Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Electrical Engineering, Systems Engineering, Control Systems Engineering, or related field.
Minimum 8 years of experience in data engineering, industrial data systems, software engineering, reliability data, or operational technology data.
Strong proficiency in SQL and Python; experience with ETL/ELT pipelines across structured, semi-structured, and time-series data.
Experience implementing data-quality validation, lineage, monitoring, error handling, and traceability controls.
Experienced in industrial and operational technology data domains including telemetry, alarms, maintenance, and asset lifecycle management.
Demonstrated ability to translate complex engineering and reliability requirements into scalable, reusable data structures and governed data products.
Skilled collaborator working across global teams including reliability, AI, and operations to deliver sustainable, production-quality engineering data solutions.