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# Log Analytics Engineer

- **Company:** OpenKyber LLC
- **Location:** Atlanta, GA, United States
- **Experience:** Experienced
- **Salary:** $135,200.0 - $156,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Software Code Optimization, Data Architecture, Information Engineering, Data Governance, Log Analysis, Machine Learning, Operational Databases, Reliability Engineering, Search Technologies, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** October 9, 2026
- **Apply:** https://www.careerjet.com/jobad/us7487a20c08b2cd328ece0a707e9f68b8

## About the Role

* 7+ years of progressive experience in data architecture, data engineering, or advanced asset analytics roles.
 * 3+ years of program or project leadership experience driving complex enterprise data solutions or asset management initiatives.
 * Proven Hands-On Databricks Expertise: Strong practical command of the Databricks Lakehouse ecosystem, Medallion Architecture, Unity Catalog, and modern ML/AI tooling.
 * Domain Knowledge: Solid understanding of reliability engineering, condition-based monitoring, predictive maintenance techniques, or enterprise asset management (EAM) concepts.
 * Preferred Experience: Direct experience working with rail infrastructure, transit networks, or linear assets.
 * Preferred Certifications: Databricks Certified Data Engineer Professional or Databricks Certified Machine Learning Professional/Associate.

## Description

* Architect & Deliver Data/AI Solutions: Lead the technical vision and end-to-end delivery of analytics, machine learning, predictive modeling, and GenAI use cases on the enterprise Databricks platform.
 * Build Scalable Data Pipelines: Design, optimize, and oversee production data pipelines utilizing Databricks Workflows and the Medallion Architecture to ingest and curate complex sensor feeds, inspection records, maintenance histories, and operational/financial datasets.
 * Advanced Predictive & Lifecycle Modeling: Guide the design and deployment of predictive health models, failure probability algorithms, and Remaining Useful Life (RUL) indicators, alongside financial lifecycle cost models for risk-based capital allocation.
 * Governance & Platform Optimization: Implement enterprise-grade data governance, lineage, and security frameworks using Unity Catalog, while continuously evaluating and integrating modern Databricks features (e.g., Delta Live Tables, MLflow, Vector Search).
 * Cross-Functional & Business Stakeholder Alignment: Partner closely with engineering, reliability, and asset management teams to deploy interactive dashboards and risk-scoring frameworks aligned with industry standards (e.g., ISO 55000) and regulatory requirements.
 * Workstream Program Leadership: Serve as a core technical anchor within the Infrastructure EAM workstream, bridging executive strategy and technical execution during high-demand project phases to reduce operational risk and project costs.