Distributed Research Platform Engineer (Quant)

PLATINUM & PARTNERS; Dubai; On-site; AED 456,000 - 480,000; Full time

Benefits offered by this job

AED 456,000–480,000 base

Discretionary bonus 20–40%

Equity-linked incentive

DIFC visa, relocation support

Job summary

PLATINUM & PARTNERS in Dubai seeks an engineer who will own the research platform, building a distributed backtesting engine and data/feature layer on cloud compute, with correctness, reproducibility and cost control at its core.

You will scale a thousand‑plus backtests, design declarative specifications for pipelines, and ensure production readiness of both research and production code, reporting directly to the founder.

Qualifications

• 4–7 years of experience building and operating distributed or batch compute for research or large-scale workloads.
• Strong production Python with NumPy, Pandas/Polars, and Arrow/Parquet.
• Cloud data engineering with BigQuery and GCS or AWS equivalents.
• Capability to work in a large statically typed codebase (C#; Java/C++ exposure acceptable).
• Willing to relocate to Dubai.

Responsibilities

• Build a distributed research engine for thousands of parallel backtests and simulations.
• Develop data and feature layer on GCS and BigQuery with versioning and lineage.
• Implement reproducibility and cost-control for cloud compute on GCP.
• Own architecture and implementation from research to production.
• Achieve production readiness within six to twelve months.

Skills

Distributed batch compute

Python for numerical work

NumPy

Pandas/Polars

Arrow/Parquet

C# (QuantConnect Lean)

Java/C++ experience

Walk-forward validation

Cloud data engineering

Tools

GCP

AWS

BigQuery

GCS

Compute Engine

Job description

PLATINUM & PARTNERS in Dubai seeks an engineer who will own the research platform, building a distributed backtesting engine and data/feature layer on cloud compute, with correctness, reproducibility and cost control at its core.

You will scale a thousand‑plus backtests, design declarative specifications for pipelines, and ensure production readiness of both research and production code, reporting directly to the founder.