Python Developer Lead

Shrewd Techlink Services; Hyderabad; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Shrewd Techlink Services in Hyderabad is seeking an experienced Python Lead to drive design and development of enterprise Python-based solutions supporting Core Banking modernization. You will build scalable data processing frameworks and cloud-native services.

The role emphasizes leadership, API development with FastAPI/Flask, real-time data streaming with Kafka, data reconciliation and automation, and collaboration with legacy teams to accelerate modernization.

Qualifications

• Experienced Python lead for enterprise-grade solutions.
• Strong background in data engineering, cloud tech and AI/ML basics.
• Proficiency with Oracle/DB2 integrations and messaging systems.

Responsibilities

• Lead design and development of Python-based applications and automation frameworks.
• Develop scalable data ingestion, transformation and migration for high-volume banking data.
• Build RESTful APIs and backend services using FastAPI or Flask.
• Design and implement Kafka producers/consumers for real-time data streaming.
• Develop automation for data reconciliation, validation, monitoring, and support.
• Integrate Python apps with Oracle, DB2, cloud platforms and messaging systems.
• Collaborate with Java, Mainframe, Data Engineering, and DevOps teams for modernization.
• Optimize performance, scalability, reliability, and observability across distributed envs.
• Mentor teams, conduct code reviews, and uphold engineering best practices.
• Support production deployments, incident resolution and continuous improvement.

Skills

Python

Data engineering

Cloud technologies

REST APIs

Kafka

AI/ML basics

Mentoring

Code reviews

Observability

Tools

FastAPI

Flask

Oracle

DB2

Job description

Role Summary: We are seeking an experienced Python Lead to drive the design and development of Python-based enterprise solutions supporting Core Banking modernization. The role involves building scalable data processing frameworks, migration automation, cloud-native services, and AI-enabled solutions to accelerate operational efficiency. The ideal candidate should have strong expertise in Python, data engineering, cloud technologies, and a foundational understanding of AI/ML and LLM technologies to support future modernization initiatives.

Key Responsibilities:

• Lead the design and development of Python-based applications, automation frameworks, and enterprise utilities.
• Develop scalable data ingestion, transformation, and migration solutions for high-volume banking data.
• Build RESTful APIs and backend services using Python frameworks such as FastAPI or Flask.
• Design and implement Kafka producers and consumers for real-time data streaming and event-driven architectures.
• Develop automation solutions for data reconciliation, validation, monitoring, and operational support.
• Integrate Python applications with Oracle, DB2, cloud platforms, and enterprise messaging systems.
• Collaborate with Java, Mainframe, Data Engineering, and DevOps teams to support legacy modernization and cloud migration initiatives.
• Optimize application performance, scalability, reliability, and observability across distributed environments.
• Mentor development teams, conduct code reviews, and establish engineering best practices.
• Support production deployments, incident resolution, and continuous improvement initiatives.

AI/ML & Intelligent Automation Responsibilities (Preferred)

• Develop AI-powered automation solutions to streamline operational workflows, data validation, and engineering productivity.
• Build and integrate Python-based services leveraging Generative AI, LLM APIs, or Retrieval-Augmented Generation (RAG) where appropriate.
• Evaluate and prototype AI/ML use cases for code generation, document processing, knowledge retrieval, log analysis, and operational insights.
• Integrate AI capabilities while ensuring compliance with enterprise security, governance, and data privacy standards, particularly for PII-sensitive environments.
• Collaborate with enterprise architecture teams to identify future opportunities for Agentic AI adoption without impacting production stability