Data Engineer
We are seeking a Data Engineer to build reliable market data, portfolio data, and risk analytics pipelines. Your work will shape the data foundation behind every model, dashboard, and client workflow we ship.
- This role is intended for candidates currently based in Malaysia and able to work without visa sponsorship.
- Proficiency in Bahasa Melayu is required (spoken and written).
- This is not a remote role. In-person client and team meetings in Klang Valley are required.
A Malaysia-based risk analytics SaaS startup.
We provide quantitative risk solutions and consulting services to financial institutions, including banks, asset managers, and insurance companies.
Our platform focuses on building industrial-grade quantitative risk engines across market risk, credit risk, liquidity risk, and climate risk, while actively integrating AI and machine learning into risk workflows. In addition to software delivery, we work closely with clients on model design, validation, stress testing, and regulatory-aligned analytics.
As a startup, we work as a small, tight-knit team. This is not an ordinary job. Every team member plays a meaningful role in shaping the product, supporting clients, and growing the company.
Clean data is a product feature.
You will build the data layer that makes quantitative risk systems trustworthy. The work spans:
You are not expected to know every financial instrument, but you should care deeply about correctness, lineage, observability, and repeatable data processing.
This role goes beyond moving rows around. You will work closely with founders, engineers, and clients to make data issues visible, explainable, and fixable.
The successful candidate must be able to attend in-person meetings in the Klang Valley when required.
What you bring.
- Strong proficiency in data engineering, analytics engineering, software engineering, or a related field.
- Good understanding of market data such as pricing data, yield curves, volatility, corporate actions, identifiers, and data quality issues.
- Experience building ETL / ELT pipelines, data validation checks, batch jobs, APIs, or analytics stores.
- Strong SQL skills and proficiency in programming for data processing, especially Python.
- Comfortable reasoning about schema design, lineage, idempotency, reconciliation, and operational failure modes.
- Basic awareness of software security and system reliability (e.g. secure coding practices, API security, data protection) is expected.
- Experience with financial instruments, portfolio systems, or risk analytics is a plus, but not required.
- Strong problem-solving ability, with attention to detail and numerical accuracy.
- Ability to communicate clearly with both technical and non-technical stakeholders.
- Professional qualifications such as FRM, CQF or CFA (completed or in progress) are an advantage but not required.
Impact matters more than job titles.
- Strong technical curiosity and willingness to learn.
- Comfortable working in a small, fast-moving team.
- Takes ownership and responsibility for outcomes, not just tasks.
- Willing to work across disciplines when needed.
- Communicates clearly and works well with others.
- Understands that in a startup, impact matters more than job titles.
Real models. Real institutions. Real ownership.
- Direct impact Be part of a startup team where your work directly affects the product and company growth.
- Real models, real clients Work on real quantitative models used by financial institutions.
- Cross-disciplinary exposure Gain exposure across quantitative modelling, AI, engineering, and data pipelines.
- Build for production Learn how systems are built, secured, and improved in a real-world environment.
- Grow with the company Opportunity to grow with the company as it scales — both technically and professionally.
Sound like you? Let's talk.
Send your CV and a few lines on your strongest area. We read every application.