Join the many companies that staff their roles with our Python engineers
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Alicia R.
- Austin, TX
- 10 years of experience
Increased API response time by 40% through code optimization and implementation of caching strategies.
Developed and maintained 15+ microservices using Python and Docker, serving over 1 million daily active users
Led a team of 5 junior developers, providing mentorship and code reviews to improve overall code quality.
Recent Project
Alicia spearheaded the development of a machine learning-powered recommendation engine for an e-commerce platform. The project involved processing large datasets, implementing collaborative filtering algorithms, and integrating the system with the existing product catalog. As a result, the platform saw a 25% increase in user engagement and a 15% boost in sales conversions.
Marcus L.
- Seattle, WA
- 12 years of experience
Reduced infrastructure costs by 30% through the implementation of serverless architecture using AWS Lambda and Python.
Automated 75% of manual testing processes, cutting QA time by half and improving overall product stability.
Contributed to open-source Python libraries, with one contribution receiving over 500 stars on GitHub.
Recent Project
Marcus recently completed a project to modernize a legacy inventory management system for a large retail chain. He led the effort to refactor the existing codebase into a more maintainable and scalable Python-based solution. The new system integrated with cloud services and real-time data processing, resulting in a 60% improvement in inventory accuracy and reduced stockouts by 40%.
Priya K.
- Chicago, IL
- 6 years of experience
Designed and implemented a data pipeline that processes over 5TB of data daily, reducing processing time by 65%.
Improved code coverage from 60% to 95% by implementing comprehensive unit and integration tests.
Developed and maintained comprehensive documentation for all major systems and APIs, facilitating easier onboarding and knowledge transfer.
Recent Project
Priya led the development of a real-time fraud detection system for a fintech startup. She utilized Python’s machine learning libraries to create predictive models that analyze transaction patterns. The system was designed to handle high-volume data streams and make instant decisions. Since its implementation, the system has successfully prevented over $10 million in fraudulent transactions.
Derek T.
- Miami, FL
- 12 years of experience
Optimized database queries, resulting in a 50% reduction in average query execution time and improved application responsiveness.
Developed a custom Python-based CRM system that increased sales team efficiency by 35% and customer retention by 20%.
Successfully migrated a monolithic application to a microservices architecture, improving scalability and ease of maintenance.
Recent Project
Derek recently completed a project to create a predictive maintenance system for a manufacturing company. He developed Python scripts to collect and analyze sensor data from industrial equipment. The system uses machine learning algorithms to predict potential failures, allowing for proactive maintenance. This resulted in a 30% reduction in unexpected downtime and significant cost savings for the company.
Olivia S.
- Boston, MA
- 12 years of experience
Implemented continuous integration and deployment pipeline, reducing deployment time by 80% and minimizing production errors by 60%.
Developed a natural language processing model with 92% accuracy for sentiment analysis of customer feedback.
Mentored junior developers in Python best practices, design patterns, and test-driven development methodologies.
Recent Project
Olivia recently led a project to develop a personalized learning platform for a major online education provider. She utilized Python to create adaptive learning algorithms that tailor content based on individual student performance. The platform integrates with various APIs to provide a seamless learning experience across devices. Since its launch, the platform has seen a 40% increase in student engagement and a 25% improvement in course completion rates.
Nexus IT Group will quickly staff your technical roles
81%
of our successful candidates are submitted within one week
92%
of our candidates will accept your offer
96%
of our candidates are employed with your firm after 12 months
What our clients have said about working with Nexus IT Group
Our client creates balance between existing investments and cloud-driven innovation with a practical approach that prioritizes results. This particular client tasked our cloud recruiters with a challenging project. Being named Google Cloud Partner of the Year, this recognition required them to increase their Google Cloud Architect and Engineering resources. Google Cloud talent is quite a bit more scarce than AWS and demand more salary, so our cloud recruiters had to get creative with our sourcing strategy. Reach out to learn how we filled 13 Google Cloud professionals for this client.
A 3 year old startup who is transforming insurance buying by providing a digital insurance engine and world-class underwriting capabilities tasked Nexus IT group to identify, vet, and hire a Head of Data Engineering for the data engineering group. Our data scientist recruiters quickly got on this executive level search. Diversity sourcing and hiring was very important for this client so the team focused on diversity sourcing. We ended up sourcing 176 candidates, submitted six candidates and the client ended up hiring one candidate.
Our client creates balance between existing investments and cloud-driven innovation with a practical approach that prioritizes results. This particular client tasked our cloud recruiters with a challenging project. Being named Google Cloud Partner of the Year, this recognition required them to increase their Google Cloud Architect and Engineering resources. Google Cloud talent is quite a bit more scarce than AWS and demand more salary, so our cloud recruiters had to get creative with our sourcing strategy. Reach out to learn how we filled 13 Google Cloud professionals for this client.
Our client creates balance between existing investments and cloud-driven innovation with a practical approach that prioritizes results. This particular client tasked our cloud recruiters with a challenging project. Being named Google Cloud Partner of the Year, this recognition required them to increase their Google Cloud Architect and Engineering resources. Google Cloud talent is quite a bit more scarce than AWS and demand more salary, so our cloud recruiters had to get creative with our sourcing strategy. Reach out to learn how we filled 13 Google Cloud professionals for this client.
Frequently asked questions about hiring your next Python engineer
Look for proficiency in Python (obviously), as well as familiarity with popular Python frameworks like Django or Flask. Knowledge of version control systems (e.g., Git), database technologies (SQL and NoSQL), and cloud platforms (AWS, Google Cloud, or Azure) is also valuable. Experience with test-driven development and CI/CD pipelines is a plus.
Consider using coding challenges or pair programming exercises. You can also ask candidates to explain complex Python concepts, such as decorators, generators, or context managers. Review their GitHub profiles or past projects to gauge their coding style and problem-solving approach.
Key soft skills include strong communication abilities, problem-solving skills, attention to detail, and the ability to work in a team. Look for candidates who can explain technical concepts clearly, as they may need to collaborate with non-technical team members.
This depends on your project needs. A generalist might be better for smaller teams or diverse projects, while a specialist could be crucial for specific domains like data science, machine learning, or web development. Consider your long-term goals and the variety of projects the engineer will work on.
While experience with specific libraries can be beneficial, it’s more important that the candidate has a strong grasp of Python fundamentals and the ability to learn quickly. Many Python libraries have similar patterns, so a skilled engineer should be able to adapt to new libraries relatively quickly.
While a degree in Computer Science or a related field can be beneficial, it’s not always necessary. Many excellent Python engineers are self-taught or have completed coding bootcamps. Focus on the candidate’s practical skills, project experience, and problem-solving abilities rather than formal education alone.
Ask to see samples of their previous work or give them a small project to complete. Look for code that is well-organized, properly commented, and follows Python’s PEP 8 style guide. You can also ask about their experience with code reviews and their approach to refactoring.
While Python 2 reached end-of-life in 2020, some legacy systems still use it. Ideally, candidates should be proficient in Python 3, but familiarity with Python 2 can be beneficial if you have older systems. Ask about their experience migrating projects from Python 2 to 3 to gauge their adaptability.
Contributions to open-source projects can be a good indicator of a candidate’s passion for programming and ability to work collaboratively. However, not all excellent engineers contribute to open source, so consider this a bonus rather than a requirement.