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Software Engineer - Data Services

GuruLink

Montreal

On-site

CAD 80,000 - 120,000

Full time

30+ days ago

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Job summary

An innovative global investment management firm is seeking an experienced Python developer to join their dynamic Data team. In this pivotal role, you will design and optimize scalable data pipelines, ensuring efficient data ingestion and transformation for financial data. Collaborating closely with quant researchers and traders, you will enhance data delivery and maintain high-performance databases. This opportunity offers the potential for growth into a leadership role, where you can mentor junior engineers and drive technical initiatives. Join a forward-thinking organization committed to leveraging technology for data-driven decision-making.

Qualifications

  • 4+ years of Python development experience, preferably 8+ years.
  • Strong grasp of object-oriented programming and SQL expertise.

Responsibilities

  • Design and optimize scalable data pipelines for financial data.
  • Collaborate with researchers and traders to improve data delivery.

Skills

Python Development
Object-Oriented Programming
SQL
ETL Pipeline Development
Data Ingestion and Transformation
Performance Tuning
Debugging and Troubleshooting

Education

Bachelor's degree in STEM

Tools

PostgreSQL
Linux

Job description

Location: Montreal, Quebec

Our client is a global investment management firm. As a technology and data-driven firm, they design and build their own cutting-edge systems, from high performance trading platforms to large scale data analysis and compute farms.

We are seeking an experienced Python developer responsible for delivering a vast quantity of data served to users worldwide. You will be a cornerstone of a growing Data team, becoming a technical subject matter expert and developing strong working relationships with quant researchers, traders, and fellow colleagues across our Technology organisation.

The ingestion pipelines and data transformation jobs are resilient and highly maintainable, while the data models are carefully designed in close collaboration with our researchers for efficient query construction and alpha generation.

You will:
  1. Design, develop, and optimize scalable data pipelines for ingesting, transforming, and serving financial data.
  2. Collaborate closely with researchers, traders, and other engineering teams to onboard new datasets and improve data delivery.
  3. Maintain and enhance distributed systems and high-performance databases, ensuring efficiency and reliability.
  4. Develop, test, and deploy software solutions in a Linux-based environment with a strong focus on automation.
  5. Debug and troubleshoot data integrity, performance, and infrastructure issues related to data pipelines.
  6. Work with internal proprietary systems and open-source tools to manage large data sets and real-time data flows.
  7. Take ownership of the production environment and participate in support rotations during business hours.
  8. Potential to grow into a leadership role, mentoring junior engineers and driving technical initiatives.
  9. Regularly take the lead on production support operations - during normal working hours only.

PLEASE NOTE: This role requires 4 days/week on-site.

Must Have Skills:
  1. Bachelor's degree in a STEM subject.
  2. 4+ years of Python development experience (8+ years preferred).
  3. Strong grasp of object-oriented programming in Python.
  4. Experience developing scalable, maintainable software systems.
  5. SQL and RDBMS expertise (PostgreSQL preferred).
  6. Strong ability to write and optimize complex queries.
  7. Understanding of indexing, partitioning, and database performance tuning.
  8. ETL pipeline development experience.
  9. Knowledge of data ingestion, transformation, and storage best practices.
  10. Hands-on experience building and managing high-throughput data pipelines.
  11. Experience developing in Linux-based environments and troubleshooting performance issues.
  12. Experience working with large-scale data systems that process high volumes of structured and unstructured data.
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