Lead Python Engineer

As a Lead Python Engineer, you will design and deliver high-quality software solutions for commercial and government clients while providing technical leadership across projects.
You will combine hands-on engineering expertise with mentorship, helping developers grow while promoting strong technical practices.
Working closely with clients and stakeholders, you will translate business objectives into scalable, secure, and effective technology solutions.
The role spans modern Python frameworks, cloud platforms, microservices, APIs, databases, containerization, and Agile delivery.
You will contribute to architecture decisions, code quality, continuous improvement, and the adoption of emerging technologies.
As part of a distributed and collaborative environment, you will have the autonomy and flexibility to make a lasting impact while continuing to grow as a technical leader.

• 6+ years of professional software development experience with a strong technical foundation.
• Advanced expertise in Python and frameworks such as Django, Flask, or FastAPI.
• Experience with microservices architecture, containerization technologies such as Docker and Kubernetes, and cloud platforms including AWS or Azure.
• Strong knowledge of RESTful API design and implementation.
• Strong understanding of object-oriented programming, design patterns, and software testing strategies.
• Strong knowledge of database design, ORMs such as SQLAlchemy or Django ORM, and SQL and NoSQL databases.
• Experience implementing secure programming practices throughout the software development lifecycle.
• Proficiency with Git-based development workflows and software development lifecycle management.
• Strong problem-solving, critical-thinking, and analytical skills.
• Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders.
• Demonstrated experience leading teams and mentoring developers in a consulting or technical environment.
• Familiarity with trunk-based development practices, including the use of feature flags, is preferred.
• Experience with application observability and instrumentation is preferred.
• Knowledge of DevOps and continuous delivery tools such as Jenkins, Harness, GitLab CI/CD, AWS Lambda, or Terraform is preferred.
• Familiarity with GenAI productivity tools such as ChatGPT, Claude, and GitHub Copilot is preferred.
• Experience with data engineering tools such as Pandas, NumPy, Spark, or Airflow is preferred.