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Data Machines Tech Stack

Cloud data analytics and DevSecOps engineering for high-stakes problems

Information Technology & Services Reston, Virginia 51–200 employees Founded 2016 Privately Held

Data Machines builds data analytics and DevSecOps solutions on cloud infrastructure, with a tech stack spanning Python, Spark, Airflow, Kafka, and Kubernetes — the backbone of distributed data platforms. Active pain points around scaling pipelines and compliance management suggest they're serving customers with complex, regulated data environments. Current hiring (7 roles in 30 days, mostly engineering and senior-level) indicates engineering-first scaling.

Tech Stack 43 technologies

Core StackLinux ServiceNow PostgreSQL Python Apache Airflow Apache NiFi Kafka Apache Spark Docker C++ Bitbucket GitLab Jenkins Podman Ansible Terraform Kubernetes Nomad Hadoop Windows SQL Jupyter Git OpenStack Packer GitLab Runner Bash Carbon Black McAfee HDFS+13 more

What Data Machines Is Building

◆Challenges

Ensuring compliance with contract requirements
Managing high-impact incidents
Process improvements for efficiency
Scaling data pipelines

▲Active Projects

Real-time query web applications
Distributed analytics platform
Data ingestion pipelines

Hiring Activity

Accelerating7 roles · 7 in 30d

Department

Engineering

3

Data

1

Ops

1

Support

1

Seniority

Senior

3

Mid

2

Junior

1

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About Data Machines

Data Machines is a data analytics and cloud architecture firm founded in 2016 and based in Reston, Virginia. The company designs and builds solutions for enterprise clients in data analytics, DevSecOps, AI/ML, and data science. Their work spans real-time query applications, distributed analytics platforms, and data ingestion pipelines — typically deployed on Kubernetes, OpenStack, or other container orchestration infrastructure. They serve organizations where compliance, incident response, and pipeline reliability are critical operational concerns.

HeadquartersReston, Virginia

Company Size51–200 employees

Founded2016

Hiring MarketsUnited States

Frequently Asked Questions

What tech stack does Data Machines use?

Python, PostgreSQL, Apache Spark, Airflow, Kafka, Kubernetes, Docker, Terraform, Jenkins, and Linux. Also deploy on OpenStack and Hadoop for distributed compute.

What is Data Machines working on?

Real-time query web applications, distributed analytics platforms, and data ingestion pipelines — typically for compliance-heavy or high-volume data environments.