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# Senior Data Platform Engineer in Seattle

- **Company:** Energy Jobline
- **Location:** Seattle, WA, United States
- **Experience:** Expert
- **Salary:** $135,000.0 - $155,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Cloud Computing, Continuous Integration, Data Governance, Data Infrastructure, Python (Programming Language), SQL Databases, Systems Integration, Terraform, Data Pipelines, Databricks
- **Published:** September 8, 2026
- **Apply:** https://www.energyjobline.com/job/senior-data-platform-engineer-seattle-31567886

## About the Role

* Hands-on Databricks experience across workspace, notebooks, and jobs, plus building platform capabilities on it (not just using it).
 * Strong Python and SQL.
 * Platform-engineering foundation: infrastructure as code with Terraform and modern CI/CD.
 * Data governance and observability in a managed environment (e.g. Unity Catalog, lineage, monitoring).
 * Strong workflow orchestration experience with Apache Airflow (we use Astro / Astronomer).
 * Building and operating data pipelines that integrate disparate, heterogeneous data sources.
 * Building reusable, self-service data products for non-engineer end users (researchers/analysts).
 * An AI-first mindset: fluent with agentic coding tools (e.g. Claude Code) and eager to make them central to how the team works. About Reply Reply specializes in the design and implementation of solutions based on new communication channels and digital media. Reply is a network of highly specialized companies supporting global industrial groups operating in the telecom and media, industry and services, banking, insurance and public administration sectors in the definition and development of business models enabled for the new paradigms of AI, cloud computing, digital media and the Internet of Things. Reply services include Consulting, System Integration and Digital Services. The base compensation range for this full-time position is between $135,000 - $155,000 plus benefits. Compensation decisions are supported through market data, where regional variances may exist based on cost of labor. We also take into consideration prior experience, relevant skills, education and/or



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