Software Engineer (TS/SCI w/ Poly) | Cloud Data Platforms

Solerity; McLean (VA); Hybrid; USD 120,000 - 150,000; Full time

Benefits offered by this job

Medical, dental, and vision

401(k) with company match

Generous PTO

Tuition assistance

Pet insurance

Employee discount program

Job summary

Solerity is seeking a Software Engineer to support a mission‑focused organization delivering data‑driven business analysis. You will build and optimize cloud‑based data processing systems, analytics platforms, and scalable environments across on‑premises and cloud infrastructures.

The ideal candidate has strong cloud, data engineering, DevOps, and automation skills, with experience in PySpark, ML model deployment, and CI/CD pipelines. Hybrid work with security clearances may apply.

Qualifications

• Bachelor's degree or equivalent in a technical field.
• Experience with cloud services (AWS) and data platforms.
• Proficiency in SQL databases and ETL workflows.
• Experience building containerized apps and CI/CD pipelines.
• Proficient in Python/Java and DevOps practices.

Responsibilities

• Develop data processing algorithms and schemas for cloud/on-prem datasets.
• Design and optimize data ingestion workflows (NiFi, Python, ETL).
• Monitor data ingest performance and quality metrics.
• Create documentation and architecture diagrams.
• Participate in full product lifecycle from design to deployment.
• Develop enterprise data architectures and enable analytics.

Skills

Cloud technologies

Data engineering

DevOps

Automation

Python

SQL

Java

Docker

CI/CD

Git

Terraform

Anaconda

PySpark

ETL

Education

Bachelor's degree in Computer Science or related

Tools

NiFi

AWS

MySQL

PostgreSQL

Docker

Terraform

GitHub

Jenkins

Jira

Confluence

Flask

Tableau

Job description

Solerity is seeking a Software Engineer to support a mission‑focused organization delivering data‑driven business analysis. You will build and optimize cloud‑based data processing systems, analytics platforms, and scalable environments across on‑premises and cloud infrastructures.

The ideal candidate has strong cloud, data engineering, DevOps, and automation skills, with experience in PySpark, ML model deployment, and CI/CD pipelines. Hybrid work with security clearances may apply.