Python Developer

Infosys; Bengaluru; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Infosys seeks a data engineer to design, develop, and maintain Python-based data processing applications. You will build ETL pipelines, optimize SQL queries, and ensure data quality across large datasets in production environments.

You will collaborate with analysts and data scientists, implement governance, and maintain documentation while working with cloud and big data technologies. Strong debugging and teamwork are required.

Qualifications

• Strong Python and SQL in production environments.
• Experience with ETL/ELT tooling and data pipelines.
• Solid understanding of data warehousing concepts (fact/dim tables, star schema).
• Ability to handle large datasets and optimize data processing workflows.

Responsibilities

• Design, develop, and maintain Python apps for data processing and automation.
• Write clean, efficient Python code and reusable modules.
• Develop ETL/ELT pipelines to ingest, transform, and load data from multiple sources.
• Design and optimize complex SQL queries, views, and stored procedures for performance.
• Perform data validation, quality checks, and reconciliation.

Skills

Python development

SQL proficiency

ETL/ELT

Data warehousing

Production experience

Data validation

Code reviews

CI/CD pipelines

Cloud platforms

Big data tech

Airflow

Tools

MySQL

PostgreSQL

SQL Server

Oracle

AWS

Azure

GCP

Spark

Hadoop

Git

Airflow

Job description

• Good understanding of SQL and data handling
• Experience working in production environments Strong proficiency in Python (data manipulation, scripting, automation) Advanced knowledge of SQL (joins, subqueries, window functions, performance tuning) Hands-on experience with ETL/ELT tools or frameworks Experience working with relational databases (e.g., MySQL, PostgreSQL, SQL Server, Oracle) Solid understanding of data warehousing concepts (fact/dimension tables, star schema) Ability to work with large datasets and optimize data processing workflows Strong analytical, problem-solving, and debugging skills
• Design, develop, and maintain Python applications
• Write clean, efficient, and reusable Python code
• Develop data processing and automation scripts
• Work with databases using SQL
• Perform code reviews and guide junior developers
• Troubleshoot application and data issues
• Support production deployments and enhancements Develop, maintain, and optimize ETL pipelines to ingest, transform, and load data from multiple sources Write efficient, scalable, and well-documented Python scripts for data processing and automation Design and optimize complex SQL queries, views, and stored procedures for performance and accuracy Perform data validation, quality checks, and reconciliation to ensure data integrity Troubleshoot and resolve data pipeline failures and performance issues Collaborate with data analysts, data scientists, and business teams to understand data requirements Implement best practices for data security, governance, and compliance Maintain technical documentation for ETL workflows and data models

• Strong experience in Python development
• Good understanding of SQL and data handling
• Experience working in production environments Strong proficiency in Python (data manipulation, scripting, automation) Advanced knowledge of SQL (joins, subqueries, window functions, performance tuning) Hands-on experience with ETL/ELT tools or frameworks Experience working with relational databases (e.g., MySQL, PostgreSQL, SQL Server, Oracle) Solid understanding of data warehousing concepts (fact/dimension tables, star schema) Ability to work with large datasets and optimize data processing workflows Strong analytical, problem-solving, and debugging skills
• Design, develop, and maintain Python applications
• Write clean, efficient, and reusable Python code
• Develop data processing and automation scripts
• Work with databases using SQL
• Perform code reviews and guide junior developers
• Troubleshoot application and data issues
• Support production deployments and enhancements Develop, maintain, and optimize ETL pipelines to ingest, transform, and load data from multiple sources Write efficient, scalable, and well-documented Python scripts for data processing and automation Design and optimize complex SQL queries, views, and stored procedures for performance and accuracy Perform data validation, quality checks, and reconciliation to ensure data integrity Troubleshoot and resolve data pipeline failures and performance issues Collaborate with data analysts, data scientists, and business teams to understand data requirements Implement best practices for data security, governance, and compliance Maintain technical documentation for ETL workflows and data models

Experience with cloud platforms (AWS, Azure, or GCP) Familiarity with big data technologies (Spark, Hadoop) Exposure to workflow schedulers (Airflow, Prefect, Cron) Knowledge of CI/CD pipelines and version control (Git) Understanding of data governance and lineage tools