Python + SQL Engineer

Role: Python SQL Engineer

Role Overview

We are seeking a skilled Python & SQL Engineer to design, develop, and maintain data-centric applications, database solutions, and automated workflows. The ideal candidate will have strong programming expertise in Python, advanced SQL skills, and experience working with large datasets. Exposure to ETL processes, data integration, and cloud technologies will be highly regarded.

Key Responsibilities

• Design, develop, and maintain scalable applications and services using Python.
• Develop, optimize, and maintain complex SQL queries, stored procedures, and database objects.
• Build and support data ingestion, transformation, and validation processes.
• Develop and maintain ETL pipelines to extract, cleanse, transform, and load data from multiple sources.
• Perform data analysis, troubleshooting, and performance tuning of databases and applications.
• Collaborate with business analysts, product owners, and technical teams to understand and implement requirements.
• Ensure data quality, integrity, security, and governance standards are maintained.
• Participate in code reviews, testing, documentation, and deployment activities.
• Support production issues and implement continuous improvements to existing solutions.

Mandatory Skills

Python

• Strong hands-on experience in Python development.
• Experience with libraries such as Pandas, NumPy, Requests, SQLAlchemy, or similar.
• Knowledge of REST APIs and automation frameworks.
• Understanding of object-oriented programming and software engineering best practices.

SQL

• Advanced SQL development skills.
• Strong experience in query optimization and performance tuning.
• Experience working with relational databases such as PostgreSQL, SQL Server, MySQL, Oracle.
• Knowledge of database design, normalization, and data modelling concepts.

Nice to Have (Advantage)

• Experience designing and supporting ETL/ELT pipelines.
• Exposure to tools such as Airflow, DBT, Informatica, Talend, Data Factory, or similar.
• Experience with cloud platforms such as AWS, Google Cloud.
• Exposure to data warehousing and analytics solutions.
• Knowledge of CI/CD, Git, and DevOps practices.
• Familiarity with PySpark or big data technologies.