Data Engineer

Python Data Engineer & Automation Developer (5–7 years of experience)

Python Development & Data Engineering

• ETL/ELT Pipeline Development: Design, develop, and maintain robust, reusable Python-based ETL/ELT pipelines to extract, transform, and load data from cloud data warehouses, specifically Snowflake.
• Data Modeling & Reconciliation: Build and optimize scalable data models, handling complex business logic, historical data snapshotting, and rigorous data reconciliation.
• Programmatic Charting & Visualization: Design and generate complex financial charts (stacked bar, line, area, and matrix heatmaps) programmatically using Python visualization libraries to embed directly into automated PDF reports.
• Automated Document Generation: Develop programmatic document generation engines (e.g., PDF/report generation using ReportLab, WeasyPrint, or FPDF2) and automate secure distribution workflows.
• General Automation & Scripting: Write clean, modular, and well-documented Python code to support diverse backend engineering, automation, and scripting tasks.
• API Integration: Design, build, and integrate custom REST APIs and connectors to sync data across disparate enterprise systems.
• Workflow Orchestration: Automate, schedule, and monitor end-to-end data workflows and system processes to ensure high availability and reliability.
• Performance Optimization: Troubleshoot, debug, and optimize database queries and Python scripts for maximum performance.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Software Engineering, Data Analytics, or a related field.
• 5–7 years of professional experience in Python development, data engineering, or backend software automation.
• 3+ years of hands-on experience writing complex SQL queries and working with cloud data warehouses (Snowflake preferred).
• Strong proficiency in Python data manipulation libraries (Pandas, NumPy) and database connectors (Snowflake Connector for Python).