Description

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

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.

Responsibilities
Robust 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.

Qualifications

Graduate/ Post Graduate

📌 Assistant Manager Bengaluru
🏢 EXL
📍 Bengaluru