Python Developer

MSH India · Bangalore, India

Python Developer – Data Platform & Middleware

MSH Business Consulting Pvt. Ltd. | Bangalore / Kolkata

Build the data backbone of MSH’s next-generation talent platform.

MSH is building an AI-first talent technology platform des igned to make sourcing, matching and hiring smarter, faster and more data-driven.

We already have platforms powering different parts of the talent ecosystem. Now, we’re building the data and middleware layer that connects them — creating a reliable shared foundation that multiple systems can work from.

We’re looking for a Python Developer who enjoys solving complex data problems, building production-grade services and working at the intersection of Python, data engineering, APIs and AI.

This is a role where you will help shape the architecture — not simply maintain an existing application.

What You’ll Work On

As part of the engineering team, you will:

• Build a shared middleware data layer connecting multiple MSH platforms
• Develop a persistent, system-agnostic Candidate ID to solve identity and deduplication challenges across systems
• Design Candidate–Job data models that track candidate stages, contact attempts and match scores for individual jobs
• Build reliable data pipelines from Snowflake and other source systems
• Identify and resolve data quality issues before they reach downstream systems
• Design data and access boundaries for client-owned and shared data
• Build APIs and services that multiple downstream systems can depend on
• Contribute to the architecture and implementation of a 16-service middleware roadmap
• Help establish the foundation for future AI/LLM-powered candidate-job intelligence

Technology You'll Work With

Core: Python, SQL, REST APIs / Services

Data: Snowflake, PostgreSQL, Cloud Data Warehouses

Orchestration: Airflow, dbt, Prefect

Cloud: AWS, GCP, Azure

DevOps: Docker, Kubernetes, CI/CD

Architecture: Data Modelling, Entity Resolution, Multi-Tenant Design

What We're Looking For

You should have:

• 4–7 years of professional Python development experience
• Strong experience building production-grade data pipelines
• Strong SQL skills
• Hands-on experience with Snowflake or a comparable cloud data warehouse
• Experience working with ETL/ELT pipelines
• Experience with Airflow, dbt, Prefect or equivalent orchestration tools
• Experience designing data models for real-world problems such as deduplication, identity resolution and unreliable source data
• Experience building REST APIs/services or backend components consumed by multiple systems
• Understanding of data privacy, access control and multi-tenant architecture
• Hands-on experience with at least one cloud platform — AWS, GCP or Azure
• Strong engineering judgment and the ability to participate in architecture and design decisions

AI-First Engineering Environment

AI is an integral part of how we expect our engineering teams to work.

Every engineer receives a monthly AI tooling budget for tools such as Claude, GitHub Copilot or equivalent.

We expect you to use AI actively in your development workflow and demonstrate how it helps you:

• Deliver faster
• Improve code quality
• Reduce bugs
• Make better technical decisions
• Explore and solve problems more effectively

You don't need to be an AI/ML specialist. We are looking for engineers who are curious about AI and know how to use it effectively in their work.

Good to Have

Experience with:

• LLM-based candidate or job scoring
• OpenAI API or similar LLM APIs
• AI-enabled data products
• Entity resolution or identity management
• Talent/recruitment technology

Why Join This Team?

Build the foundation, not just features

You'll be working on the core data architecture that future MSH talent intelligence capabilities will depend on.

Solve real engineering problems

Messy identities, inconsistent data, multiple systems and complex client boundaries — this is production engineering, not a tutorial project.

Influence architecture

You'll have the opportunity to contribute to technical decisions and challenge existing approaches when you see a better way.

Work AI-first

You'll have access to the tools and budget to make AI a meaningful part of your engineering workflow.