Job Description

Responsibilities:

• Translate reporting requirements into modular, reusable Python classes and scripts.
• Build automation workflows by using Python.
• Read JSON input files.
• Dynamically construct and execute SQL queries against our database.
• Invoke calculation modules to cleanse, transform, and compute derived metrics.
• Embed calculation outputs into specified PowerPoint slide shapes using python-pptx.
• Upload completed presentations to Google Drive via the Google Drive API.
• Implement robust error handling, logging, and retry mechanisms to ensure production reliability.
• Parameterize and configure scripts to support different report types and inputs without code changes.
• Use Git (or similar VCS) to manage deployment and scheduling of automated jobs.
• Monitor script performance; optimize Python code for speed and scalability.
• Document solution architecture, data flows, module interfaces, and configuration options.
• Collaborate with stakeholders to validate results and refine requirements.
• Stay up-to-date with Python best practices, key libraries (pandas, SQLAlchemy, python-pptx, google-api-python-client), and automation trends.

Required Qualifications:

• Bachelors degree in Computer Science, Data Science, Engineering, or related field (or equivalent experience).
• 13 years of hands-on Python development, including object-oriented design.
• Proven experience building Python-driven reporting or data-processing automations.
• Proficient in Python data and automation libraries (e.g., pandas, NumPy, SciPy, python-pptx, google-api-python-client, etc.).
• Hands-on experience integrating with Google APIs (Drive, Sheets, etc.).
• Solid data analysis foundation: cleansing, transformation, aggregation, and basic statistics.
• Proficient with Git or similar version control systems.
• Excellent problem-solving skills and attention to detail.
• Strong written and verbal communication; able to document and present technical solutions.

Preferred (Nice-to-Have)

• SQL skills; comfortable writing and optimizing complex queries.
• Familiarity with scheduling or orchestration tools (cron, Airflow, etc.).
• Basic experience with Docker and CI/CD concepts.
• Background in writing unit or integration tests for Python code.
• Exposure to BI/reporting tools (Tableau, Power BI).

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