Python Software Engineer IV
Menlo Park, CA Remote OR preferred onsite (hybrid)
Position Overview
We are seeking a Software Engineer to support data processing and application development initiatives. The ideal candidate will be responsible for building reliable web-scraping scripts, optimizing data workflows with SQL, and delivering high-quality, maintainable code in a collaborative engineering environment.
Key Responsibilities
Design and deploy efficient Python scripts to parse and download large-scale web datasets.
Construct and optimize complex SQL queries for downstream data processing and analytics.
Author clean, performant, and well-maintained code adhering to established software engineering standards.
Participate actively in peer code reviews and drive continuous improvement in development best practices.
Diagnose, troubleshoot, and resolve software defects to ensure high system reliability and performance.
Maintain comprehensive technical documentation to support application sustainability.
Communicate technical updates and collaborate effectively with cross-functional stakeholders and team members.
Required Qualifications
Bachelor’s degree in Computer Science, Software Engineering, or a related technical discipline.
6+ years of professional experience in software engineering.
Advanced proficiency in Python development.
Strong practical experience operating within Linux environments and writing shell scripts.
Solid proficiency in constructing and optimizing SQL queries.
Proven problem-solving capabilities, analytical acumen, and rigorous attention to detail.
Demonstrated ability to deliver results both independently and within collaborative project teams.
Experience contributing to large-scale software development initiatives.
Preferred Qualifications
Master’s degree in Computer Science or a related technical field.
Demonstrated experience in web scraping and processing large-scale datasets.
Hands-on experience with cloud infrastructure platforms (e.g., AWS, Google Cloud Platform, Azure).
Familiarity with DevOps methodologies, CI/CD, and infrastructure tools.
Foundational understanding of data analytics and machine learning concepts.
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