Senior Data Platform Engineer - Python & AWS

United Kingdom | Oct. 5, 2026

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Company: Permutable

Country: United Kingdom

Type: Hybrid remote

Employment: Full-time

Description:

At Permutable, we’re building real-time AI systems that turn large volumes of global news, market and proprietary data into market intelligence and systematic signals for financial institutions.

We’re looking for an experienced Data Platform Engineer with strong Python and AWS skills to build and scale the systems behind our data ingestion, processing, storage and delivery.

You’ll write production Python, develop reliable data pipelines and own the AWS infrastructure that runs them. As we move towards a more real-time, event-driven architecture, you’ll help shape how data flows through our platform and reaches our models and clients.

Working directly with our founder and engineering team, you’ll have significant responsibility for architecture, implementation and production performance.

Build production data pipelines: Design and develop Python services and pipelines to ingest, validate, transform and deliver large volumes of news, market and proprietary data.

Develop our AWS data platform: Build and scale infrastructure across S3, RDS/PostgreSQL, Lambda, ECS and EKS, choosing the right services for each workload.

Build event-driven systems: Develop services using messaging, queues and asynchronous processing to support faster data updates and reliable distributed workflows.

Improve data quality and reliability: Build validation, deduplication, schema handling, retries and recovery into our pipelines. Make it straightforward to identify missing data, investigate failures and reprocess historical datasets.

Own storage and data access: Improve how we store, query and serve data to support research, production models and client-facing applications.

Support AI and quantitative workloads: Work with AI engineers and researchers to provide reliable data inputs and integrate NLP, LLM and quantitative model outputs into the platform.

Automate infrastructure and deployments: Manage infrastructure through Pulumi and build CI/CD workflows using GitHub Actions.

Monitor and optimise production: Develop monitoring and alerting for pipeline health, data freshness and service performance. Diagnose production issues and improve processing speed, resilience and AWS costs.

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