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# Big Data Architect

- **Company:** Gigatec Llc
- **Location:** Annapolis Junction, MD, United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Confluence, JIRA, Bash Shell, Big Data, Information Engineering, Linux, Python (Programming Language), Software Engineering, Delivery Pipeline, Apache Spark, Git, Containerization, Atlassian Tools, Software Version Control, Docker
- **Published:** June 2, 2026
- **Apply:** https://www.careerjet.com/jobad/usc3faba61ab1562f57010779abc610e99

## About the Role

* Experience using the Linux CLI and Linux tools
 * Experience developing Bash scripts to automate manual processes
 * Recent software development experience using Python and Java
 * Experience using Apache Airflow (DAG design, scheduling, operators, sensors) to orchestrate, schedule, and monitor complex workflows
 * Experience using Distributed Big Data processing engines including Apache Spark
 * Experience with containerization technologies such as Docker, containerd, and Podman
 * Experience with Git Source Control System, * Familiar with AWS Cloud Services and Infrastructure
 * Experience using the Atlassian Tool Suite (JIRA, Confluence)
 * Fluent in sarcasm, kindness, and the occasional office banter

## Description

What You'll Be Doing (We don't love the bullet points, but we love the work!) In this key Software Engineer role, you'll be responsible for creating and maintaining data workflows and automation pipelines using Apache Airflow, keeping critical processes flowing as smoothly as a well-timed morning coffee. This role focuses on building reliable, scalable, and observable workflow orchestration solutions that support data engineering, analytics, and operational use cases, because no one wants a pipeline that is more decaf than dependable. You'll get to collaborate with data engineers, platform teams, and stakeholders to ensure workflows are efficient, secure, and production ready, delivering results with the consistency of a favorite espresso order.


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