Python Technical Lead

Company Description

LeanQubit is a Certified Integrator of Ignition, specializing in the manufacturing, energy, and utility industries. Our certification ensures expertise in understanding business fundamentals and applying Ignition-based solutions that fit specific needs. We provide flexible, cost-effective hardware solutions integrated with our proprietary FactoTools to enable automation and drive business results. Located in Mumbai, we maintain our certification for the latest Ignition software to offer cutting-edge solutions.

Job Summary:

We are seeking a highly skilled and experienced Python Technical Lead to drive the development of scalable, high-performance software systems. The ideal candidate will have deep expertise in Python programming, data structures, memory optimization, database engineering, and machine learning/AI integration. You will lead a team of engineers, architect robust solutions, and ensure the delivery of high-quality, production-grade software. 

Key Responsibilities:

• Lead the design, development, and deployment of complex Python-based software systems. 
• Architect scalable, low-latency systems for high-volume, high-frequency data processing. 
• Optimize Python applications for performance, memory usage, and concurrency. 
• Design and manage efficient, scalable database architectures. 
• Integrate machine learning models into production systems and pipelines. 
• Collaborate with cross-functional teams including data scientists, DevOps, and product managers. 
• Conduct code reviews, mentor team members, and enforce engineering best practices. 
• Stay current with emerging technologies and recommend adoption where appropriate. 

Technical Skills Required:

Programming & System Design:

• Expert in Python, including advanced features such as generators, decorators, context managers, and metaclasses. 
• Strong grasp of data structures and algorithms for performance-critical applications. 
• Experience with asynchronous programming using asyncio and concurrent.futures. 
• Proficient in memory management, profiling, and optimization using tools like memory_profiler, objgraph, and tracemalloc. 
• Designing for low-latency, high-throughput, and real-time processing. 
• Experience with distributed systems, microservices, and event-driven architectures. 

Database Engineering:

• Advanced experience with relational databases: PostgreSQL, MySQL, SQLite. 
• NoSQL databases: MongoDB, Cassandra, Redis. 
• Query optimization, indexing, partitioning, sharding, and replication. 
• Data modeling for both OLTP and OLAP systems. 
• Experience with streaming data and time-series databases (e.g., InfluxDB, Apache Druid). 

Machine Learning & AI:

• Experience working with data scientists to integrate ML models into production systems. 
• Familiarity with ML frameworks: TensorFlow, PyTorch, Scikit-learn. 
• Understanding of model serving (e.g., TensorFlow Serving, ONNX, TorchServe). 
• Experience with feature engineering, data pipelines, and model versioning. 
• Exposure to computer vision, NLP, or predictive analytics is a plus. 

Cloud & DevOps:

• Hands-on with AWS, Azure, or GCP. 
• CI/CD pipelines: Jenkins, GitHub Actions, GitLab CI. 
• Containerization: Docker, Kubernetes. 
• Infrastructure as Code: Terraform, Ansible. 

Testing & Quality:

• Unit and integration testing: unittest, pytest, mock. 
• Performance testing: Locust, JMeter. 
• Code quality tools: flake8, pylint, black. 

Collaboration & Agile:

• Git-based version control (GitHub, GitLab, Bitbucket). 
• Agile/Scrum methodologies. 
• Tools: JIRA, Confluence, Slack, Miro. 

Preferred Qualifications:

• Experience in real-time analytics, financial systems, or IoT platforms. 
• Certifications in Python, cloud platforms, or ML/AI. 
• Strong communication, leadership, and mentoring skills.