Data Developer (Financial Services)

certus recruitment group โ€ข Australia
Remote
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AI Summary

Design, build, and operate a modern data platform for a hedge fund. Develop and maintain scalable Python-based ETL pipelines and cloud-based data lake solutions. Collaborate with portfolio managers and quantitative researchers to deliver tailored data solutions.

Key Highlights
Develop and maintain scalable Python-based ETL pipelines
Build and manage cloud-based data lake solutions
Collaborate with portfolio managers and quantitative researchers
Key Responsibilities
Develop and maintain scalable Python-based ETL pipelines for ingesting and transforming large-scale market data
Build and manage cloud-based data lake solutions 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
Technical Skills Required
Python Pandas Linux AWS Databricks Kafka
Benefits & Perks
$100K-$150K base + super
100% remote
Permanent Full-Time Role
Nice to Have
Kafka
LLMs, AI/ML integration
Cloud experience (AWS / Azure)
Experience working in hedge funds, prop trading, or quantitative finance environments

Job Description


Data Developer (Financial Services A MUST)

๐Ÿ“ Melbourne / Sydney Location ONLY (But role is 100% remote)

๐Ÿ’ฐ $100K โ€“ $150K base + super

๐Ÿง‘ ๐Ÿ’ผ Permanent Full-Time Role (real time data via market feeds experience required)


We are seeking a 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.


Youโ€™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


  • Bachelorโ€™s degree (or higher) in Computer Science, Engineering, Mathematics, Statistics, or related quantitative discipline
  • 2+ yearsโ€™ experience developing Python-based data or financial systems (At least 2 years of relevant experience in developing python-based financial software) Financial Services a MUST
  • Real time data via market feeds experience required
  • Strong Python skills, including data manipulation using Pandas
  • Exposure to financial datasets across multiple asset classes
  • 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



Interested candidates with full Australian working rights are encouraged to apply and join a growing, forward-thinking team.


Please email me your CV to c.thum@certusrecruitment.com then give Charmaine Thum a call on 0439 320 538


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