Lead Python Engineer - Director - Equities

Lead Python Engineer - Greenfield Equity Data Platform - Director

Location: London (Hybrid)
Type: Permanent

Overview

A leading global Investment Bank is embarking on a major greenfield build out of an Equity Data Platform as part of a multi year strategic data transformation programme for the Equities business. This is a rare opportunity to take a foundational engineering role, shaping the platform architecture, technology choices, and long term roadmap from day one.

You will be at the centre of a high impact initiative to design and deliver a scalable, cloud ready data platform supporting Equities trading, research, analytics, and risk. As the platform grows, you will also have the opportunity to build and lead a team from the ground up, helping to define engineering culture, processes, and best practices.

The Role

This is a hands on senior engineering position focused on delivering a modern Python based data ecosystem for the bank's Equity business lines. You'll collaborate with trading, quant, and data strategy teams to build high performance data pipelines, ingestion frameworks, transformation layers, APIs, and services.

Key Responsibilities

• Build and architect a greenfield Equity Data Platform supporting trading, analytics, and regulatory workflows.
• Design and implement Python based data services, frameworks, and pipelines across structured and unstructured datasets.
• Establish modern engineering practices across testing, automation, CI/CD, observability, and deployment.
• Define data models, ingestion strategies, patterns, and storage architectures.
• Drive adoption of scalable cloud ready solutions aligned with the bank's overall data strategy.
• Collaborate with quants, trading desks, data engineers, and platform teams to deliver performant, reliable systems.
• Take a leadership role in growing and mentoring a new engineering team as the platform matures.
• Influence long term architectural decisions and technology choices across the data estate.

Key Skills & Experience Essential

• Strong experience building large scale Python data platforms, pipelines, or backend services.
• Proven background in high performance, mission critical environments (ideally Equities, trading, or financial data).
• Experience with modern data engineering tooling (streaming, orchestration, storage, APIs).
• Strong understanding of data modelling, ETL/ELT pipelines, and data lifecycle management.
• Knowledge of distributed systems, microservices, or cloud native architectures.
• Experience implementing testing, CI/CD, and automation in modern engineering setups.
• Excellent communication skills with the ability to work closely with Front Office and quant stakeholders.

Desirable

• Experience in Equities or Equity Derivatives data sources, analytics, or trading workflows.
• Exposure to cloud platforms (Azure, AWS, or GCP).
• Experience hiring, mentoring, or leading small engineering teams.
• Familiarity with Apache Spark, Kafka, Delta Lake, or similar data technologies.

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