Overview
SOSi is seeking Data Engineers to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in Huntsville, Alabama.
This role will be responsible for delivering automation to key national security missions interacting with petabyte-scale data on supercomputing resources.
In this role, you will construct data analytical infrastructure, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis.
You will leverage scientific techniques to transform petabyte-scale data into insightful data products to enable data-driven decisions.
You will partner with Data Scientists to refactor manual workflows to produce highly automated MLOPs based workloads. You will perform using scrumban techniques and be embedded with end users.
The team will work with technologies including :
- Open source, Commercial, and Government software packages such as Kafka, Beam, NumPy, Kubeflow, Nvidia Triton, PyTorch, TensorFlow, Weaviate, Neo4j, Grafana, etc.
- Cloud native techniques and containerization with Docker
- Infrastructure as Code with Terraform
- Configuration as Code with OPA
- Observability with tools like EFK and LOKI + OTel
- Leverage GitOps patterns and CI / CD with tools like GitLab, Argo, and Harness
- Perform SAST / DAST security with tools like SonarQube
- Perform Kubernetes and K3s orchestration with tools like Rancher and Konvoy
SOSi is seeking data talent to unlock insights from massive datasets supporting strategic national security objectives. If you have a passion for data science and want to apply your skills to impactful projects at scale, we want to hear from you!
Essential Job Duties
- Build and maintain data pipelines, ETL processes, and storage systems
- Develop services and extend infrastructure to enable machine learning workflows
- Integrate software components into functional data systems
- Write clean, testable, maintainable code in Python and other languages
- Implement CI / CD pipelines and DevSecOps best practices
- Create technical documentation for software systems
- Collaborate across teams to share knowledge and leading practices
Minimum Requirements
- Top Secret Security Clearance
- Experience in data engineering and / or software development
- Expertise with Python, GIT, YAML, Docker, and SQL
- Knowledge of CI / CD, DevSecOps, and Agile methodologies
- Experience developing back-end systems and services
- Understanding of software design and system integration
Preferred Qualifications
- Top Secret Security Clearance with SCI eligibility
- Experience as a Site Reliability Engineer (SRE)
- Experience with AIOps and FinOps
- Experience with Petabyte scale data sets
- Experience with large-scale, multi-INT analytics
- BS or MS in Computer Science, Statistics, Mathematics, Physics or a quantitative field
Work Environment
- Working conditions are normal for an office environment.
- Fast paced, deadline-oriented environment.
- May require periods of non-traditional working hours including consecutive nights or weekends (if applicable).
SOSi is an equal employment opportunity employer and affirmative action employer. All interested individuals will receive consideration and will not be discriminated against on the basis of race, color, religion, sex, national origin, disability, age, sexual orientation, gender identity, genetic information, or protected veteran status.
SOSi takes affirmative action in support of its policy to advance diversity and inclusion of individuals who are minorities, women, protected veterans, and individuals with disabilities.
- Top Secret Security Clearance
- Experience in data engineering and / or software development
- Expertise with Python, GIT, YAML, Docker, and SQL
- Knowledge of CI / CD, DevSecOps, and Agile methodologies
- Experience developing back-end systems and services
- Understanding of software design and system integration
- Build and maintain data pipelines, ETL processes, and storage systems
- Develop services and extend infrastructure to enable machine learning workflows
- Integrate software components into functional data systems
- Write clean, testable, maintainable code in Python and other languages
- Implement CI / CD pipelines and DevSecOps best practices
- Create technical documentation for software systems
- Collaborate across teams to share knowledge and leading practices
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