Data Engineer - Designs data pipelines and architectures for clean, usable analytics.
Build scalable analytics, monitoring, and correlation solutions across CAE, Mission Control, and other SPT platforms to turn large engineering and operational datasets into actionable insights.
Core Skills
• Advanced SQL
• Python
• Data analysis and transformation
• Large-scale data processing
• Data modeling
• Dashboard and visualization development
• Statistical analysis and anomaly detection
• ETL / ELT pipelines
• Working with time-series and manufacturing/test data
• API-based data integration
Strongly Preferred
• Databricks
• AWS
• Splunk
• Power BI
• Microsoft Fabric
• Pandas / PySpark
• Machine learning or pattern-detection experience
• Manufacturing, test, telemetry, or semiconductor datasets
• Experience correlating multiple enterprise data sources
• AI/LLM-assisted analytics or agentic workflows
Expected Responsibilities
• Analyze CAE, manufacturing, test, telemetry, and operational datasets.
• Build analytics for Mission Control covering yield, power, thermal, NVLink, diagnostics, inventory, and other engineering signals.
• Develop automated detection of anomalies, outliers, drift, clusters, and trends.
• Correlate data across sources such as SFC, TestLogs, BOM, diagnostics, shipping, and issue-tracking systems.
• Create dashboards, reports, alerts, and drill-down analytics.
• Develop reusable datasets and data models for engineering teams.
• Partner with subject-matter experts to define meaningful metrics and detection criteria.
• Support AI/agent-based analytics while keeping engineering decisions under human review.
• Improve data quality, performance, and accessibility for downstream applications.
.png?format=webp)
