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# SENIOR DATA ENGINEER

- **Company:** Kforce Inc.
- **Location:** Huntsville, AL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Amazon Web Services, Big Data, Command-Line Interface, Cloud Computing, Cloud Database, Databases, Data Validation, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Systems, Relational Databases, Linux, Distributed Computing Environment, Distributed Data Store, PostgreSQL, Linux System Administration, Operational Databases, Performance Tuning, Scala (Programming Language), PL-SQL, SQL Databases, Data Streaming, Systems Integration, Data Logging, Data Processing, Scripting, Enterprise Software Applications, Data Ingestion, Informatica Powercenter, Apache Spark, Database Performance, Backend, Apache Nifi, Data Pipelines
- **Published:** October 28, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9269870/senior-data-engineer

## About the Role

Senior-level professional experience in Data Engineering, ETL Development, Data Integration, or closely related engineering roles.
Strong hands-on development experience with Java.
Experience developing and supporting data solutions within AWS.
Strong experience designing, developing, and maintaining ETL/ELT pipelines.
Hands-on experience with Apache Spark and Scala for distributed data processing.
Advanced experience with SQL and PL/SQL, including complex querying and performance optimization.
Experience working with PostgreSQL or comparable enterprise relational database technologies.
Hands-on experience developing data flows using Apache NiFi.

Experience developing or supporting ETL integrations using Informatica.

Strong knowledge of Linux environments, command-line utilities, scripting, and troubleshooting.

Demonstrated experience with data pipeline development, optimization, tuning, monitoring, and production support.

Experience processing and integrating large, complex datasets from multiple source systems.

Strong understanding of data transformation, data quality, schema design, relational databases, and distributed data-processing concepts.
Core Technical Stack

Java | AWS | ETL/ELT | Spark | Scala | SQL | PL/SQL | PostgreSQL | Apache NiFi | Informatica | Linux | Data Pipelines | Data Integration | Performance Tuning

## Description

We are seeking a Senior Data Engineer to design, develop, optimize, and maintain enterprise-scale data pipelines and data integration solutions. This role requires strong hands-on experience with Java, AWS, ETL, Apache Spark, Scala, SQL/PLSQL, PostgreSQL, Apache NiFi, Informatica, and Linux.

The ideal candidate has deep experience building production data pipelines, integrating complex data sources, troubleshooting data-processing issues, and optimizing pipelines for performance, reliability, and scalability., Design, develop, deploy, and maintain high-volume data pipelines and ETL/ELT workflows supporting mission-critical applications and analytics.
Develop data engineering solutions using Java, including backend processing, data transformation, integration, and automation components.
Build and maintain cloud-based data processing solutions within AWS environments.
Develop distributed data-processing workloads using Apache Spark and Scala.
Design, develop, and optimize complex SQL and PL/SQL queries, procedures, transformations, and data-processing routines.
Work extensively with PostgreSQL and relational database platforms to support data ingestion, transformation, storage, and retrieval.
Develop and maintain automated data flows and integrations using Apache NiFi.
Build and support enterprise ETL and data integration workflows utilizing Informatica.
Design pipelines that ingest and transform data from multiple structured and semi-structured data sources.
Perform hands-on pipeline optimization, performance tuning, troubleshooting, and root-cause analysis across large-scale data environments.
Identify and resolve data-processing bottlenecks involving queries, transformations, pipeline architecture, compute resources, and database performance.
Develop reliable processes for data validation, error handling, monitoring, logging, and recovery.
Work in Linux-based environments, including scripting, troubleshooting, deployment, and application/data-processing support.
Improve pipeline scalability, resiliency, efficiency, and maintainability as data volume and processing requirements increase.
Collaborate with software engineers, database engineers, cloud engineers, analysts, and other technical teams to integrate data across enterprise systems.
Support production data environments and troubleshoot complex issues across applications, databases, ETL platforms, pipelines, and cloud infrastructure.