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# Data Pipeline Engineer

- **Company:** Kforce Inc.
- **Location:** Washington, DC, United States
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Big Data, C++ (Programming Language), Computer Networks, Information Engineering, Extract Transform Load (ETL), Software Debugging, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Operational Data Store, Operational Databases, Data Streaming, Data Processing, Data Ingestion, Delivery Pipeline, Pyspark, Api Design, Code Restructuring, Data Pipelines
- **Published:** June 25, 2026
- **Apply:** https://www.clearancejobs.com/jobs/8992855/data-pipeline-engineer

## About the Role

Strong experience with large-scale data engineering and ETL/ELT workflows
Proficiency in Python and distributed data processing frameworks (PySpark preferred)
Solid understanding of dataframes and data manipulation at scale
Experience troubleshooting production data pipelines and debugging failures
Knowledge of relational databases and SQL fundamentals
Familiarity with distributed computing concepts

Additional Technical Exposure

Experience with Java or similar languages (C++ acceptable alternative)
Ability to diagnose and resolve memory/performance issues in distributed jobs
Exposure to visual pipeline tools or data workflow platforms is helpful
Basic understanding of networking concepts and API-based data ingestion

Operational Environment, Strong foundation in data engineering within production environments
Experience supporting operational data systems rather than purely building new solutions
Comfortable working in high-volume, incident-driven environments
Able to quickly understand and troubleshoot unfamiliar systems
Hands-on experience with distributed data processing and large datasets

## Description

This role is heavily focused on maintaining and stabilizing large-scale data pipelines in a production environment. The majority of time is spent troubleshooting and resolving issues across existing data workflows rather than building new systems.
Early success in this position looks like gaining enough familiarity with the platform, data flows, and key stakeholders to independently diagnose and resolve pipeline failures across multiple environments., Investigate and resolve data pipeline failures across multiple production environments
Perform root cause analysis on data quality and pipeline performance issues
Apply targeted code fixes and adjustments to restore pipeline functionality
Monitor pipeline health and respond to alerts within defined SLAs
Support and maintain existing ETL processes rather than developing new ones
Refactor pipelines to resolve performance issues such as memory constraints or inefficient processing
Coordinate with upstream data providers and internal teams to resolve data ingestion issues
Escalate issues when access, ownership, or dependencies fall outside immediate control

Day-to-Day Breakdown

~85-90%: Debugging, incident response, and pipeline issue resolution
~5-10%: Monitoring, validation, and health checks
~5-10%: Minor code updates, optimizations, and pipeline adjustments

Work is centered on fixing and stabilizing existing pipelines, not building new ones from scratch., Engineers support a large number of pipelines across multiple environments simultaneously
Work is highly reactive, driven by incoming alerts and data incidents
Engineers are expected to quickly assess and troubleshoot pipelines they have not previously worked on
High alert volume, with multiple issues often tied to common root causes

Collaboration

Frequent interaction with data providers to resolve source data issues
Regular coordination with cross-functional technical teams on pipeline failures
Occasional engagement with end users reporting data discrepancies

On-Call & Incident Response

Rotating on-call schedule supporting different pipeline groups
Some rotations may include off-hours alerts tied to overnight pipeline processing
Majority of incidents handled during business hours, with occasional escalation scenarios
Engineers are expected to own resolution when possible and coordinate when dependencies exist


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