Lead Backend Engineer / Developer (Python + Java + Cloud) - Manager

Vibehackers; India; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Vibehackers seeks a Lead Backend Engineer to design and implement scalable Python and Java backend services and RESTful microservices for financial data and quantitative models. You will lead data modeling, time-series analysis and end-to-end infrastructure for data gathering, cleaning, signal generation and model implementation in a financial services setting.

You will collaborate with global teams across cloud (AWS/Azure) and on-prem environments, overseeing deployment, release engineering and

Qualifications

• 10–14 years IT experience with leadership/lead engineer background.
• Strong Python and Java skills with emphasis on Python core concepts.
• 5+ years Python backend development with NumPy, Pandas, matplotlib, Scikit-learn.
• Experience with REST APIs, microservices, and cloud/on-prem environments.

Responsibilities

• Design, implement and deploy scalable enterprise web applications and RESTful APIs using microservices.
• Lead data modeling, develop analytical data models, perform time-series data analysis and data anomaly detection.
• Implement backend computation pipelines and automate advanced data processing for standalone execution.
• Build end-to-end infrastructure for data gathering, cleaning, signal generation and model implementation.
• Work with global teams on design, release engineering, deployments and support following company standards.
• Troubleshoot production issues, perform root cause analysis and maintain operational stability.
• Communicate project plans and technical details with counterparties across regions and collaborate with other teams to improve solutions.

Skills

Data Modeling

Time Series Analysis

REST API Development

Microservices

Backend Development (Python/Java)

Cloud Platforms (AWS/Azure)

Distributed Agile

Leadership/Team Management

Communication

Release Engineering

Tools

Databricks

Job description

Lead Backend Engineer to design and implement scalable Python and Java backend services and RESTful microservices for financial data, time-series analysis, and quantitative model implementation. The role focuses on data modeling, large-scale data processing, and deployment across cloud (AWS/Azure) and on-prem environments, collaborating with global teams. Vibe coding is explicitly required.

Job Description

Role

Lead Backend Engineer (Manager) responsible for backend service development, data modeling, time-series analysis, and building end-to-end infrastructure for data gathering, cleaning, signal generation and model implementation in a financial services environment.

Key Responsibilities

• Design, implement and deploy scalable enterprise web applications and RESTful APIs using microservices.
• Lead data modeling, develop analytical data models, perform time-series data analysis and data anomaly detection.
• Implement backend computation pipelines and automate advanced data processing for standalone execution in controlled environments.
• Build end-to-end infrastructure for data gathering, cleaning, signal generation and model implementation.
• Work with global teams on design, release engineering, deployments and support following company standards.
• Troubleshoot production issues, perform root cause analysis and maintain operational stability.
• Communicate project plans and technical details with counterparties across regions and collaborate with other teams to improve solutions.

Requirements

• 10-14 years of IT experience; leadership/lead engineer experience expected.
• Strong programming and design skills in Python and Java; expert understanding of Python core concepts, functional and class-based design.
• 5+ years of Python backend development experience; demonstrable experience with common Python packages such as NumPy, Pandas, matplotlib, SAlib, Scikit-learn.
• Experience implementing REST APIs and microservices; experience with cloud platforms (AWS or Azure) and on-prem environments.
• Experience with RDBMS such as Oracle, SQL Server, and Postgres; familiarity with Databricks.
• Strong quantitative and mathematical background; experience or familiarity with finance domain and statistical concepts preferred.
• Experience with distributed Agile and Lean practices, release engineering, and managing large datasets and computationally intensive tasks.

Good to Have

• MLOps and quantitative mathematical model development experience across multi-asset data.
• Experience in quantitative financial research, market data analysis, and familiarity with vendor pricing/fundamentals datasets.
• 4-5 years of buy-side or sell-side research experience is desirable.

Work Schedule & Location

• Primary team location: Cambridge (just off Harvard Square), USA; business/technology teams also present in India, UK, Poland, China.

Notes

• Must be able to manage multiple projects/tasks and deadlines while maintaining attention to detail.
• Expected to establish processes for working with very large datasets and optimize repetitive/computationally intensive tasks.

Skills

Data Modeling Time Series Analysis REST API Development Microservices Backend Development Quantitative Analysis Release Engineering Deployment Troubleshooting Root Cause Analysis Distributed Agile Lean Practices Project Management Collaboration Communication Process Establishment