Data analyst/Data Engineer
Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Oct 17, 2026. SEGULA Technologies scores A on the Alion truth index.
Position Summary
The Lead Product Development Data Engineer owns key data processes and analytics applications within the broader Product Development Process (PDP). In this cross-functional role, you will bridge the gap between Engineering and enterprise organizations-including IT, Manufacturing, Finance, Purchasing, and Supply Chain-to establish standardized, high-performing data workflows, modern cloud architectures, and scalable analytics solutions.
Key Responsibilities
1. Data Architecture & Cloud Engineering
Enterprise Platform Management: Build, optimize, and maintain big data pipelines and architectures leveraging Snowflake, Databricks, or Microsoft Fabric.
Cloud & Data Pipelines: Design scalable data models and storage solutions (Lakehouse, DirectLake) using SQL, Python, PySpark, and cloud ecosystems across Azure or AWS.
Modern Analytics Integration: Migrate legacy data workflows to modern cloud architectures, establishing robust data governance, pipeline security, and data lineage.
2. Process Governance & Analytics Standards
Process Ownership: Drive global uniformity, documentation, and continuous refinement across assigned Product Development processes and digital applications.
Business Intelligence & Dashboards: Develop, deploy, and maintain executive-level dashboards and reporting tools using Power BI, PowerApps, and Palantir Foundry.
Workflow Automation: Streamline administrative and operational cross-functional engineering tasks using Power Automate and Microsoft 365 tools.
3. Cross-Functional Leadership & AI/ML Support
Stakeholder Alignment: Collaborate across IT, Manufacturing, Finance, Purchasing, and Program Management to capture technical requirements and align business goals.
AI/ML Workflows: Support the integration of machine learning models and predictive analytics into existing engineering data pipelines.
Executive Communication: Translate complex data technicalities and process trade-offs into clear decision packages, business cases, and leadership presentations.