Python Engineer

About Man Group

Man Group is one of the world’s largest active investment management firms, focused on delivering attractive performance and client portfolio solutions, and deploying the latest technology across our business to help ensure we stay at the forefront of our evolving industry. Across our investment managers, we provide long-only, alternative and private markets products.

Our clients, and the millions of pensioners and savers that they represent, are at the very centre of everything we do. Our mission is to deliver value-added investment outcomes to those retirees and savers so that they are able to enjoy better long-term retirement conditions. We underpin this focus with our commitment to operating a socially aware and responsible business.

The Role

We’re looking for a high-performing software engineer to join the engineering team of Man Group’s central data platform, named Codex. Projects don’t get much more cross-cutting or high-profile than this: we have hundreds of internal users and whatever you work on will be used by teams across the business for years to come. Fundamentally, we are not a data engineering team: we empower our userbase to become data engineers with our software. This is a great time to join the team as we consider how to expand our offering to the entire business with some true greenfield projects. There are three main pillars of the Codex platform:

• Data Acquisition - an ETL/ELT platform for research and production which scales to multi-terabyte datasets; and can index all data at Man for re-usability and discoverability.
• Data Governance - cataloguing the thousands of datasets at Man; allowing discovery, entitlements, data quality, and end-to-end data lineage.
• Data Delivery - providing a unified interface across the thousands of datasets across Man with a focus on scaling, identifier mapping, and UX.

Technology and Business Skills

We strive to hire only the brightest, best and most highly skilled, passionate technologists.

Essential

• 2-4 years of professional experience in software engineering, ideally in Python.
• Proven track record of collaborating effectively in cross-functional teams, with excellent communication skills.
• Experience building reliable, production-grade applications.
• In-depth working knowledge of one or more relevant database technologies such as Snowflake, PostgreSQL, Iceberg, or MongoDB.
• Strong interest in tackling data challenges at scale.
• Mastery of (at least) one programming language, modern software engineering principles, and clean code practices.

Advantageous

• Comfortable working on Linux platforms and using Git
• Expertise in modern data engineering practices including ELT/ETL tools, distributed storage & processing, and data lakehouses. (Please note that we provide these tools for others rather than using them!)
• Expertise in Python and proficiency with scientific libraries such as Pandas, NumPy, SciPy, statsmodels and scikit-learn
• Experience in quantitative software development within a front-office setting, such as at a hedge fund, proprietary trading firm, or investment bank
• Experience working with large data sets, both structured and unstructured
• Experience building web applications using modern frameworks like React
• Proficient with distributed computing technologies such as Spark, Dask, Kubernetes, Redis
• Strong understanding of financial markets and instruments
• Experience working with financial market data
• Relevant mathematical knowledge e.g., statistics, time-series analysis

Personal Attributes

• Strong academic record and a degree with high mathematical and computing content e.g., Computer Science, Mathematics, Engineering or Physics
• Intellectually robust with a keenly analytic approach to problem solving
• Self-organised with the ability to effectively manage time across multiple projects and with competing business demands and priorities
• Focused on delivering value to the business with relentless efforts to improve process
• Strong interpersonal skills: able to establish and maintain a close working relationship with quantitative researchers, portfolio managers, traders and senior business people alike
• Confident communicator: able to argue a point concisely and deal positively with conflicting views

Our Technology

Our systems are almost all running on Linux and most of our code is in Python, with the full scientific stack: numpy, scipy, pandas to name a few of the libraries we use extensively. We implement the systems that require the highest data throughput in Java. Within Data Engineering we use Pandas, Dataiku, Snowflake, Prometheus, and ArcticDB heavily.