Senior Data Developer (Financial Services A MUST)
Melbourne / Sydney Location ONLY (But role is 100% remote)
$150K – $200K base + super
Permanent Full-Time Role
We are seeking a Senior Data Developer for a hedge fund to design, build, and operate a modern data platform that powers quantitative research, trading, and risk management across multiple asset classes. This role sits within a central data engineering team at the intersection of data engineering and software development, where you will own end-to-end data pipelines, build next-generation security master systems, and ensure high‐quality, reliable data delivery to support investment and trading decisions.
You'll work in a fast‐paced, high-performance environment where data quality, speed, and scalability directly impact research and trading outcomes.
Key Responsibilities
* Develop and maintain scalable Python‐based ETL pipelines for ingesting and transforming large‐scale market data from multiple sources
* Build and manage cloud‐based data lake solutions (AWS / Databricks) for structured and unstructured data storage and retrieval
* Implement robust data quality, validation, and cleansing frameworks to ensure accuracy of financial time‐series data
* Optimise data workflows for low latency and high throughput to support quantitative research, trading, and risk functions
* Collaborate closely with portfolio managers, quantitative researchers, and traders to deliver tailored data solutions for modelling and strategy development
* Contribute to the design and enhancement of the security master database
* Analyse large datasets to generate insights that inform trading and risk decisions
* Document system architecture, data flows, and technical solutions to ensure transparency, scalability, and reproducibility
Requirements
* Bachelor's degree (or higher) in Computer Science, Engineering, Mathematics, Statistics, or related quantitative discipline
* 5+ years' experience developing Python‐based data or financial systems; Financial Services a MUST
* Strong Python skills, including data manipulation using Pandas
* Exposure to financial datasets across multiple asset classes
* Experience working with quantitative analysts or research teams
* Strong understanding of Linux environments
* Solid foundation in mathematics and statistics
* Ability to thrive in fast‐paced, high‐pressure environments
* Strong problem‐solving and communication skills (written and verbal)
Nice to Haves
* Experience with Kafka or other streaming technologies
* Understanding of financial market data, symbology, and reference data across equities, futures, credit, indices, and OTC markets
* Experience working in hedge funds, prop trading, or quantitative finance environments
* Cloud experience (AWS / Azure)
* Exposure to LLMs, AI/ML integration, or modern data/AI architecture
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