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# Data Engineer Advisor

- **Company:** NTT DATA, Inc.
- **Location:** Atlanta, GA, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $208,000 - $228,800
- **Contract:** Permanent contract
- **Skills:** Microsoft Azure, Cloud Database, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Structures, Data Transformation Services, Data Warehousing, Python (Programming Language), Power BI, SQL Databases, Data Processing, Data Ingestion, Azure Data Factory, Apache Spark, Git, Microsoft Fabric, Data Lakes, Pyspark, Information Technology, Tools for Reporting, Data Pipelines
- **Published:** November 5, 2026
- **Apply:** https://www.atlantacareerpath.com/job.asp?id=3496652789&tx=FK1916FFG&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

3+ years of Data Engineering, ETL/ELT, or cloud data development experience.

3+ years of Strong hands-on experience with SparkSQL, PySpark, Delta Tables, Pipelines, and Fabric Notebooks.

3+ years of Experience with Microsoft Fabric, Azure data services, SQL, and modern Lakehouse/data warehouse concepts.

3+ years of Experience with Git, CI/CD, data quality, and production support practices.

Bachelor's degree in Computer Science, Data Engineering, Information Technology, Engineering, or a related field, or equivalent professional experience.

Preferences

3+ years of Experience with OneLake, Fabric Lakehouse, Fabric Data Warehouse, and Azure Data Factory.

3+ years of Experience supporting Power BI and enterprise semantic/reporting solutions.

3+ years of Experience with Azure DevOps, Delta Lake, and large-scale enterprise datasets.

Work Environment

This is a fully remote position. Candidates must be comfortable collaborating with business, product, data, engineering, QA, and other stakeholders in a distributed environment.

## Description

Design, develop, and maintain scalable data pipelines and data transformation solutions.

Develop data processing logic using Python, PySpark, SparkSQL, and SQL.

Build and optimize Delta Tables and Lakehouse data structures for analytics and reporting.

Develop, schedule, monitor, and troubleshoot Pipelines for data ingestion and transformation.

Create and maintain Fabric Notebooks for data engineering, transformation, and automation workloads.

Partner with architects, analysts, and Power BI teams to deliver reliable, high-quality enterprise data solutions.