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# Senior Software Engineer - Spark & Airflow Data Pipelines

- **Company:** CTRL,  LLC
- **Location:** Fort Meade, MD, United States (Remote available)
- **Experience:** Expert
- **Salary:** $257,150 - $283,941
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Bash Shell, Distributed Computing Environment, JSON, Job Scheduling, Python (Programming Language), PostgreSQL, Linux Commands, MariaDB, MySQL, NumPy, SQL Databases, Unstructured Data, Extensible Markup Language (XML), Parquet, Apache Spark, Jupyter, Git, Pandas, Information Technology, Atlassian Tools, Slurm, Data Pipelines
- **Published:** November 5, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=e2ceb401f1ad46d7

## About the Role

Applicants must currently hold an active TS/SCI with polygraph. Ctrl+ does not sponsor new security clearances or clearance upgrades. Applicants who do not meet this requirement cannot be considered., * 7 years of relevant experience with a Bachelor's degree in Computer Science or a related discipline (5 years with a Master's, or 9 years without a degree).

 * Linux command-line tools
 * Bash scripting
 * Recent Python and Java development
 * Apache Airflow DAG design, scheduling, operators and sensors
 * Apache Spark or similar distributed processing engines
 * SQL with MySQL, MariaDB or PostgreSQL
 * Jupyter, pandas and NumPy
 * Parquet, JSON, CSV and XML data
 * Git

Preferred qualifications

 * Slurm or other HPC job schedulers
 * Jira and Confluence

## Description

Design the data pathways that keep analytics moving. Build reliable ingest and egress flows powered by Spark and Airflow.

The mission

Support distributed data processing and analytics workloads that help mission teams work with large, varied datasets.

What you'll do

 * Design and optimize data ingress and egress pathways
 * Build and tune Apache Spark distributed processing jobs
 * Orchestrate and monitor workflows with Apache Airflow
 * Wrangle structured, semi-structured and unstructured data
 * Apply data quality, validation and anomaly detection practices