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 Cades. The projects are very comprehensive and have a significant impact on the company. We are looking for someone with experience with our technology stack or with engineering teams within Man Group.

Tasks

The tasks include:

• Data Engineering: Working on ETL/ELT pipelines for research and production that scale to multi-terabytes and index all data from Man for reusability and discoverability
• Data Science: Collaborating with Man’s thousands of data assets to enable discovery, enrichment, data quality, and end-to-end data provenance
• Data Delivery: Providing a unified interface for Man's thousands of datasets, with a focus on creating better experiences through datasets, APIs, and a data lake

technology

Almost all of our systems run on Linux, and most of our code is written in Python, using the full scientific stack. Our data engineering team uses a variety of libraries, including:

• Pandas
• Databricks
• Snowflake
• Prometheus
• Airflow/Prefect

We also use Kafka for data pipelines, Python and Spark for ETL, Bitbucket for source code management, Jenkins for continuous integration, Grafana + Prometheus for metrics collection, ELK for log shipping and monitoring, Docker for automation, Kubernetes for container orchestration, and Slack for internal communication.

Requirements

Essential:

• Expertise in software engineering, ideally in Python
• Demonstrated ability to work collaboratively in teams
• Familiarity with one or more database technologies such as Snowflake, Postgres/SQL, or similar
• 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:

• Challenges in Developing Scalable Production-Grade Applications
• Convenience when working on Linux platforms and using Git
• Experience with Python and/or libraries such as Pandas, NumPy, SciPy, and statmodels
• Knowledge of financial markets and instruments
• Experience working with financial data
• Relevant mathematical knowledge, e.g., statistics, time series analysis

Personal characteristics

• Strong academic background and a degree with a high mathematical and computer science content, e.g., computer science, mathematics, engineering, or physics
• Analytical thinking combined with a creative and systematic approach to problem-solving
• Self-motivated with the ability to effectively manage time across multiple projects and competing business requirements and priorities
• Focused on delivering