Associate Python Engineer

The role

We are looking for a high-performing Associate Software Engineer to join our engineering team. The team works on Man Group’s central data platform, called Codec. The projects are very comprehensive and high-profile, as we have hundreds of internal teams, and everything you develop will be used by teams across the company for years to come.

Tasks and requirements

The Codec platform has three main components: * Data Ingestion – ETL/ELT pipelines for research and production that can scale to multi-terabytes and index all data at Man * Data Catalog – enables the use of thousands of datasets at Man, including discovery, permissions, data quality, and end-to-end data lineage * Data Delivery – provides a unified interface for thousands of datasets at Man, with a focus on usability, standard interfaces and APIs, and user interfaces

technology

Almost all of our systems are built on Linux, and most of our code is written in Python, using the full scientific stack. We use:

• Pandas, Databricks, Snowflake, Prometheus, and Airflow
• Kafka for End-to-End ETL
• Bitbucket for source code management
• Jenkins for continuous integration
• Grafana + Prometheus for metric collection
• ELK for log shipping and monitoring
• Docker for containerization and orchestration
• Kubernetes for container orchestration and automation, and Click for internal communication

Requirements

Essential:

• Expert knowledge of software engineering, ideally in Python
• Proven ability to work collaboratively in teams
• Familiarity with one or more database technologies such as Snowflake, PostgreSQL, or NoSQL
• A genuine interest in tackling data challenges on a large scale
• Proficiency in at least one programming language, modern software engineering principles, and clean coding practices
• Understanding of the fundamentals of software testing, including the testing pyramid

Advantageous:

• Experience in developing reliable, production-ready applications
• Working Safely on Linux Platforms and with Git
• Experience with Python or similar libraries such as Pandas, NumPy, SciPy, and statmodels
• Experience in the quantitative/finance field with quantifiable portfolios and self-directed learning
• An interest in quantifiable software development in a front-office environment
• Experience with large volumes of data, both structured and unstructured
• Experience with technology applications that use Python or similar languages
• Familiarity with distributed computing technologies such as Spark, Dark, Kubernetes, and Redis
• A solid understanding of financial markets and instruments
• Experience with financial market data
• Relevant mathematical knowledge, e.g., statistics, time series analysis

Personal characteristics

• A strong academic background and a degree with a significant focus on mathematics and computer science
• Self-motivated with a sharp analytical approach to problem-solving
• Self-organized with the ability to effectively manage time across multiple projects and competing business requirements and