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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.
Job Responsibility:
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
Requirements:
Significant experience as a Data Engineer or advanced analytical role
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
Active Secret security clearance with ability to obtain TS/SCI with CI polygraph
Nice to have:
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
What we offer:
Competitive salaries
Continuing education assistance
Professional development
Multiple healthcare benefits package options
401K with employer matching
Competitive time off policy along with a federally recognized holiday schedule