Data Solutions Architect

2 weeks ago

Narrabri, Australia beBeeQuantitative Full time $120,000 - $160,000
Quantitative Trader Analyst

This role is an exciting opportunity for a skilled Python developer to join our team in creating cutting-edge trading infrastructure.

Job Description:

Our client leverages petabyte-scale data to drive global high frequency trading strategies. This position sits at the intersection of trading, data infrastructure, and quantitative research, where you'll work directly with traders, quants, and developers to build scalable data pipelines, integrate structured/unstructured datasets, and optimize high-performance querying systems—all while shaping the future of real-time trading infrastructure.

Key Responsibilities:

  • Own and optimize large-scale data pipelines (petabyte-scale data lakes) feeding into trading strategies.
  • Design and implement high-performance ETL workflows, integrating diverse data sources (market data, alternative datasets, unstructured feeds).
  • Collaborate with quants and traders to translate research concepts into efficient, scalable data solutions.
  • Develop tooling for real-time data validation, monitoring, and visualization to ensure data integrity.
  • Enhance our proprietary data platform using modern open-source technologies (e.g., distributed compute, cloud-native services, containers, streaming frameworks).
  • Solve complex data challenges—low-latency processing, schema design for time-series data, and optimizing queries across massive datasets.

Required Skills and Qualifications:

  • Strong Python development skills, with expertise in data libraries like Pandas, NumPy, PySpark, or Dask.
  • Experience with large-scale data systems (SQL/NoSQL databases, distributed processing, or cloud data platforms).
  • Proven ability to own data pipelines end-to-end—from ingestion to analytics-ready outputs.
  • Familiarity with modern data stack tools (e.g., Airflow, Kafka, Kubernetes, Iceberg/Databricks, or similar).
  • Understanding of financial markets/trading data (tick data, order books, reference data).
  • Strong collaboration skills—able to work with quants, traders, and infra teams.

Nice-to-Have Qualifications:

  • Experience with real-time data systems (stream processing, WebSocket APIs).
  • Knowledge of quantitative finance concepts (alpha research, signal generation).
  • Background in performance optimization (query tuning, parallelization, caching).
  • Exposure to CI/CD, DevOps practices, or infrastructure-as-code.
Becoming part of this dynamic team will bring numerous benefits, including:
  • The opportunity to work on cutting-edge technology and solve complex data challenges.
  • The chance to collaborate with experienced professionals in the field.
  • A fast-paced environment that fosters growth and learning.
  • Professional development opportunities to enhance your skills and career.

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