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# Senior Specialist - Data Engineering

- **Company:** LTM Inc
- **Location:** Charlotte, NC, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Big Data, Information Engineering, Data Governance, Distributed Computing Environment, Apache Hadoop, Hadoop Distributed File System, Apache Hive, Performance Tuning, Sqoop, Unstructured Data, Data Processing, Data Ingestion, Apache Spark, Pyspark, Data Pipelines
- **Published:** August 6, 2026
- **Apply:** https://us.experteer.com/career/view-jobs/senior-specialist-data-engineering-charlotte-nc-usa-58819674

## About the Role

_ of experience with HDFS, Hive and Spark * strong hands-on experience in the Hadoop ecosystem (on-premise) * expertise in PySpark for large-scale data processing * experience building and optimizing Spark jobs * hands-on data ingestion experience with Sqoop * good understanding of distributed data processing and big data concepts * ability to design, develop and maintain scalable data pipelines * experience with large volumes of structured and unstructured data * strong problem-solving skills and independence in fast-paced environments * exposure to cloud platforms (AWS/Azure/GCP) is a plus Key requirements *

## Description

Experteer Overview As a Data Engineer, you will design, develop and maintain scalable data pipelines in on-premise Hadoop environments. You will work with PySpark, HDFS and Hive to process large-scale data and optimize Spark jobs. You'll troubleshoot data pipelines, enforce data quality practices, and collaborate with cross-functional teams to enable reliable data-driven decisions. This role focuses on hands-on implementation and performance tuning in a fast-paced setting, with exposure to cloud platforms as a plus. Compensation / Benefits * design and maintain scalable data pipelines * develop and optimize Spark jobs (PySpark) * work with HDFS and Hive for data processing and warehousing * data ingestion and integration using Sqoop * troubleshoot data pipeline issues and performance bottlenecks * enforce data quality governance and best practices * support onprem Hadoop ecosystem architectures and tuning * collaborate with stakeholders in fast-paced environments Tasks * 5+ years of experience with HDFS, Hive and Spark * strong hands-on experience in the Hadoop ecosystem (on-premise) * expertise in PySpark for large-scale data processing * experience building and optimizing Spark jobs * hands-on data ingestion experience with Sqoop * good understanding of distributed data processing and big data concepts * ability to design, develop and maintain scalable data pipelines * experience with large volumes of structured and unstructured data * strong problem-solving skills and independence in fast-paced environments * exposure to cloud platforms (AWS/Azure/GCP) is a plus Key requirements *


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