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# Senior Data Engineer in United

- **Company:** Energy Jobline
- **Location:** Carbon, WV, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Microsoft Azure, Software as a Service, Databases, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Fault Tolerance, Python (Programming Language), Key Management, Microsoft SQL Server, Power BI, Data Logging, Build Management, Microsoft Fabric, Data Management, Hardware Infrastructure, Data Pipelines, Container Apps, Key Vault
- **Published:** October 27, 2026
- **Apply:** https://www.energyjobline.com/job/senior-data-engineer-united-32074745

## About the Role

* 5-8 years of hands-on data engineering in production environments
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 * Proven track record delivering data platforms on Azure and/or AWS
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 * Experience migrating legacy on-premises infrastructure to cloud- solutions
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 * Hands-on experience with Azure Container Apps Jobs or a comparable containerized job execution platform
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## Description

We're looking for a Senior Data Engineer to design, build, and operate modern data platforms at scale. You'll work across Azure, Microsoft Fabric, and AWS - building reliable pipelines, performant data models, and self-service analytics that drive real business decisions. A core part of this role is containerized workload execution: designing and deploying pipeline jobs using Azure Container Apps Jobs for scheduled and event-driven processing. This is a hands-on role for an engineer who thrives in ambiguity, values clean architecture, and moves comfortably between strategy and implementation., n
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 * Develop Python-based ETL/ELT pipelines ingesting data from APIs, flat files, databases, and SaaS platforms
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 * Build and deploy containerized jobs using Azure Container Apps Jobs, including scheduling, scaling rules, secrets management (Key Vault), and Container Registry integration
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 * Maintain data movement between on-premises SQL Server and cloud targets
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 * Design idempotent, fault-tolerant pipeline patterns with robust logging, alerting, and retry logic
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 * Partner with analytics teams to deliver clean, well-documented data models for Power BI and similar BI tools
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