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# Data Engineer (onsite)

- **Company:** The Joule
- **Location:** Atlanta, GA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $140,000.0 - $155,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Microsoft Azure, Big Data, Cloud Database, Cloud Engineering, Information Systems, Databases, Continuous Integration, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Systems, Document-Oriented Databases, Python (Programming Language), Meta-Data Management, NoSQL, Standard Sql, Software Engineering, SQL Databases, Systems Integration, Data Logging, Azure Data Factory, Information Technology, Integration Frameworks, Data Pipelines, Databricks
- **Published:** September 18, 2026
- **Apply:** https://www.dice.com/job-detail/aeff34a7-e26e-4acd-8fe0-d67bc9dc6a2d

## About the Role

* 8+ years of experience in data engineering, software engineering, or database architecture
 * 6+ years of experience in Python and SQL with experience building scalable ETL/ELT pipelines
 * 2+ years of experience with cloud data ecosystems like Azure Data Factory
 * 1+ years of experience with modern data processing frameworks like Databricks
 * Experience with integrating and transforming data from diverse formats and systems (APIs, flat files, relational sources)
 * Knowledge of relational and NoSQL databases, data modeling, and schema design
 * Knowledge of data governance, security, and compliance principles for enterprise data environments
 * Ability to support on-site work in Atlanta, GA or Washington, DC
 * Bachelor's degree in computer science, Engineering, Information Systems, or a related, quantitative field

## Description

* Design, implement, and maintain enterprise grade ETL/ELT pipelines using Python and SQL
 * Build, optimize, and manage data models, warehouses, and lakehouse environments (e.g., Databricks)
 * Develop processes for ingesting, cleaning, validating, and transforming large-scale datasets from APIs, relational sources, and unstructured systems
 * Implement data quality, metadata management, and governance controls to ensure consistency and trust in analytics workflows
 * Collaborate with cloud engineering teams to deploy and manage data solutions on Azure
 * Monitor, troubleshoot, and improve pipeline performance using logging, alerting, and CI/CD practices
 * Document data architecture, pipeline logic, and operational procedures to enable team collaboration and maintainability


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