Senior Python Developer

Senior Python Developer

Role Overview

We seek a seasoned Senior Python Developer with expertise in Pandas, SQL databases, and Azure to design, develop, and optimize data-intensive applications. You'll architect robust ETL pipelines, enhance data models, and ensure seamless cloud integration to support our data-driven initiatives.

Key Responsibilities

• Design, develop, and maintain Python-based applications and microservices.
• Build and optimize ETL pipelines using Pandas, NumPy, and SQLAlchemy for data processing, transformation, and analysis.
• Manage SQL databases (e.g., PostgreSQL, MySQL, SQL Server), including schema design, query optimization, and performance tuning.
• Deploy and manage cloud-native solutions on Microsoft Azure (e.g., Azure Functions, Azure SQL, Azure Data Factory, Blob Storage).
• Implement data validation, testing, and monitoring frameworks to ensure data integrity and system reliability.
• Collaborate with data scientists, analysts, and engineers to translate business requirements into scalable technical solutions.
• Mentor junior developers and advocate for best practices in coding, security, and CICD.

Required Skills / Qualifications

• Experience 10 years in Python development, with 3 years focused on data engineering/analytics.
• Technical Expertise
• Python Ecosystem Proficiency in Pandas, NumPy, and data manipulation libraries.
• Databases Advanced SQL skills (complex queries, indexing, stored procedures) and ORM tools (e.g., SQLAlchemy).
• Cloud Hands-on experience with Azure services (e.g., Azure Functions, Azure SQL, Data Lake, Synapse).
• Data Pipelines Experience building batchreal-time ETL workflows.
• Tools Git, Docker, CICD pipelines (e.g., Azure DevOps), and LinuxUnix environments.
• Soft Skills Strong problem-solving, communication, and teamwork abilities.
• Education Bachelors degree in Computer Science, Engineering, or a related field.

Preferred Skills

• Azure certifications (e.g., Azure Data Engineer, Azure Developer).
• Experience with PySpark, Apache Airflow, or Kafka.
• Knowledge of NoSQL databases (e.g., Cosmos DB).
• Familiarity with DevOps practices (IaC, Terraform).
• Exposure to machine learning frameworks (e.g., scikit-learn).