
Senior Backend Engineer
- Remote
- Delhi, Delhi, India
- Pondicherry, Tamil Nādu, India
- Ahmedabad, Gujarāt, India
- Fatorda, Goa, India
- Hyderabad, Telangāna, India
- Bangalore, Karnātaka, India
- Indianapolis, Indiana, United States
- Mumbai, Mahārāshtra, India
- Sahibzada Ajit Singh Nagar (Mohali), Punjab, India
+8 more- Engineering
Job description
At TechBiz Global, we provide recruitment services to our TOP clients from our portfolio. We are currently seeking a Senior Backend Engineer to join one of our clients’ teams - a Singapore-based FinTech company connecting global investors with private debt opportunities across Southeast Asia.
The successful candidate will work on a Private Credit Investment Platform and Credit Analytics Platform, developing scalable solutions and working with financial and loan data.
What You’ll Do
Design and develop scalable backend solutions for the Private Credit Investment Platform.
Build solutions to ingest, process, and analyse loan book and financial data.
Collaborate with product managers, designers, and engineers to translate business requirements into technical solutions.
Participate in code reviews and provide constructive feedback.
Take ownership of technical solutions and contribute to product development.
Manage multiple priorities and deliver high-quality results.
Support the technical direction and continuous improvement of the platform.
Job requirements
What We’re Looking For
At least 3–4 years of software development experience.
Strong experience with Golang, Java, or a similar backend programming language.
Experience with cloud platforms such as AWS, GCP, or Azure.
Experience with MongoDB or other non-relational databases.
Strong problem-solving and analytical skills.
Good communication and teamwork skills.
Ability to work independently and take ownership of tasks.
Nice to Have
Previous experience in the FinTech or financial services industry.
Strong hands-on experience with Golang and MongoDB.
Knowledge of Apache Parquet or similar technologies.
Experience working with data-intensive applications.
Experience processing large financial datasets.
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