Assistant Manager

We’re looking for a strong Python engineer to help modernize legacy data workflows into production-grade Python pipelines running in a cloud-based data environment.

The role focuses on building reliable, scalable, and highly validated data pipelines with structured configs, logging, parquet-based processing, and lightweight Streamlit interfaces. A major part of the work involves translating existing workflow logic into clean, vectorized Python while ensuring data accuracy and consistency across large datasets.

• Strong Python + pandas expertise (vectorized, memory-aware, production-grade)
• Solid SQL fundamentals
• Data validation & edge-case handling (null joins, leading zeros, dtype drift, precision, encoding, sort stability)
• Performance optimization using profiling and benchmarking tools
• Clean engineering practices: reusable code, documentation, testing, and backward compatibility

Tech stack includes:

• Python,
• pandas,
• PyArrow/parquet,
• SQL,
• Google APIs,
• Tableau integrations,
• Streamlit,
• openpyxl, and XML parsing

Experience with PySpark, Polars, DuckDB, or large-scale data processing is a plus.

You should be comfortable reading complex data flows, debugging silent data issues, optimizing slow transformations, and shipping maintainable pipeline code.

Graduate/ Post Graduate