Python Developer

Infosys; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Infosys in Bengaluru seeks a data engineer with strong Python development and advanced SQL skills to design, develop, and maintain scalable data pipelines for large-scale datasets.

You will work on ETL/ELT workflows, optimize queries, and collaborate with data analysts to ensure data quality, governance, and reliable production deployments.

Experience with cloud platforms (AWS/Azure/GCP), Spark or Hadoop, and workflow schedulers (Airflow) is a plus, with emphasis on code quality and documentation.

Qualifications

• Strong analytical, problem-solving, and debugging skills.
• Experience in production environments.
• Design, develop, and maintain Python applications and ETL pipelines.

Responsibilities

• Design, develop, and maintain Python applications and data processing scripts.
• 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.
• Maintain technical documentation for ETL workflows and data models.
• Collaborate with data analysts, data scientists, and business teams to understand data requirements.

Skills

Python development

SQL

ETL/ELT

Data warehousing

Data validation

Debugging

Code reviews

Production deployments

Data governance

Tools

MySQL

PostgreSQL

SQL Server

Oracle

Airflow

Git

AWS

Azure

GCP

Spark

Hadoop

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