Data Analytics Engineer

The Data Analytics Engineer will be responsible for:

Design and implement automated test scripts using Python, leveraging libraries like Pandas, NumPy, and SciPy for data manipulation, analysis, and visualization of engine performance metrics.
Utilize version control systems, particularly Bitbucket (or Git), for collaborative code development, branching, merging, and pull requests.
Analyze and interpret test data to identify trends, anomalies, and areas requiring further investigation.
Identify, document, and track defects using appropriate tools.
Collaborate with development teams to troubleshoot and resolve issues.
Participate in code and design reviews to provide feedback on testability and potential issues.
Improve testing processes and methodologies, advocating for best practices.
Communicate test results and findings to stakeholders, including technical and non-technical audiences.

Qualifications
Bachelor's Degree in Computer Science, Software Engineering, or a related engineering field
At least 5 years of work experience in a data-driven professional setting
Data analysis experience in Python programming, including experience with data analysis libraries and test automation frameworks
Experience with Agile development methodologies and tools such as Jira and Bitbucket.
Experience with analytical methodologies and the desire to solve new technical challenges
Experience with data analysis tools and techniques, including data manipulation, visualization, and statistical analysis
Solid understanding of debugging and root cause analysis.
Self-starter who can work well within a team or independently with minimal oversight
U. S. Citizenship is required
Position requires the ability to obtain a U. S. Government Security Clearance, if needed Candidates selected may be subject to a U. S. Government security investigation and must meet eligibility requirements for access to classified information. For more information on Security Clearances, please visit: S. Department of State