About MBIG
MBIG helps clients build scalable cloud and AI-enabled applications that solve real business problems. You’ll work closely with product teams and clients across industries to design, build and support high-performance backend systems and analytics pipelines.

Role overview
As a Senior Python Developer / Consultant at MBIG, you’ll lead the design and delivery of backend services, data-processing pipelines, and APIs. You’ll mentor engineers, contribute to architecture decisions, and ensure high code quality in an Agile delivery environment.

Key responsibilities

• Lead design and implementation of new solutions using Python and modern frameworks (Django/Flask).
• Build reusable, well-tested, high-performance server-side components and APIs.
• Design and develop Spark-based data processing jobs and ETL pipelines.
• Write and optimize complex SQL queries and assist in database schema design.
• Troubleshoot and resolve production issues; implement monitoring and observability.
• Collaborate with product owners, QA, and DevOps to deliver features under Agile/Scrum.
• Mentor junior developers and run code reviews to maintain code quality and best practices.
• Explore and introduce relevant new technologies to improve solution efficiency and scalability.

Required experience & education

• Bachelor’s degree in Computer Science, Engineering, or related field. Master’s preferred.
• 3–4 years total IT experience with minimum 4 years in Python development.
• Strong hands-on experience with Python (3.x), writing clean, reusable, testable code.
• Experience with Apache Spark (PySpark) for large-scale data processing.
• Solid SQL skills — ability to write and optimize complex queries and design schemas.
• Experience building RESTful APIs using Django or Flask.
• Understanding of concurrency/threading in Python, async patterns is a plus.
• Familiar with unit testing (pytest/unittest), CI/CD practices and version control (Git).

Preferred / nice-to-have

• Experience with cloud platforms (AWS/Azure/GCP) and containerization (Docker, Kubernetes).
• Knowledge of message queues (Kafka, RabbitMQ) and microservices architecture.
• Familiarity with monitoring tools (Prometheus/Grafana), logging and observability.
• Exposure to ML model deployment or MLOps workflows (bonus).

What we offer

• Opportunity to work on impactful projects for diverse clients.
• Collaborative Agile teams, mentorship, and learning budget.
• Flexible work arrangements and performance-linked growth.