Python Database Engineer

Project Overview

Prestigious Client / Project: Contributing to a high-scale data platform for a leading telecom giant. This strategic project focuses on enhancing location-based intelligence and spatial data processing at scale.
Revolutionizing Technologies: Work on cutting-edge backend systems involving GIS-based spatial databases, PostgreSQL/PostGIS, Python (Flask/Django), REST APIs, advanced data modeling, ETL pipelines, and database performance tuning.Agile Development: Agile methodologies drive fast-paced development cycles, continuous collaboration, iterative delivery, and seamless integration with cross-functional data teams to meet high-performance and scalability goals

Role and Responsibilities

• Design, implement, and manage PostgreSQL/PostGIS databases with spatial data
• Optimize spatial queries, indexing strategies, and overall DB performance
• Work on data modeling, partitioning, and replication/failover setup
• Develop backend services using Flask/Django and integrate with REST APIs
• Build and maintain ETL pipelines and handle large datasets efficiently
• Ensure data integrity, conduct database testing, and support analytical needs
• Collaborate with data teams to meet performance and scaling goals
• Maintain clear documentation and contribute to continuous process improvements
  

Requirements

Mandatory Skills

• SQL & PostgreSQL (PostGIS): Strong hands-on experience with relational and spatial databases, including writing complex queries and managing geospatial data.
• Spatial Data Modeling & Optimization: Ability to design and optimize spatial data structures for performance and accuracy.
• Indexing & Performance Tuning: Skilled in indexing strategies and tuning database queries for optimal speed and efficiency.
• Flask or Django: Backend development experience using at least one Python web framework for building APIs or services.
• REST API Integration: Ability to build and consume RESTful APIs for application communication.
• ETL Pipeline Development: Experience in building and managing data pipelines to extract, transform, and load data efficiently.
• Database Testing: Ensuring data quality, consistency, and performance through rigorous testing practices.
• Problem-Solving & Analytical Skills: Strong ability to troubleshoot, analyze data issues, and optimize system performance.

Good-to-Have Skills

• Data Partitioning & Sharding: Knowledge of scaling databases by splitting data logically or physically.
• High Availability (Replication/Failover): Experience with fault-tolerant database setups for continuous service availability.
• Domain Knowledge GIS: Understanding of GIS-based applications and use cases to align with project needs.