Senior Backend Engineer, Data Pipelines & AI Platforms

Dex; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

Dex is a partner-led company building an AI-powered platform to transform messy data into automated pricing, inventory, and distribution insights. You will own end-to-end data ingestion, workflow orchestration, and backend service architecture from the ground up.

You will partner with founders and ship resilient ingestion pipelines, observable DAG-based workflows, and scalable Python APIs. This role demands ownership, high initiative, and comfort in a fast-moving startup context.

Qualifications

• Substantial production experience designing, building, and operating backend systems and APIs in Python.
• Hands-on ownership of end-to-end data pipelines and workflow orchestration engines such as Airflow or custom DAG-based systems.
• Deep experience tackling messy integrations across legacy protocols, on-prem databases, SFTP feeds, and unstructured file dumps.
• High agency and comfort operating with early-stage startup intensity, shaping architectural foundations without predefined playbooks.

Responsibilities

• Architect and operate resilient ingestion pipelines that ingest, clean, and transform messy customer data across legacy ERPs, on-prem databases, and flat files.
• Design and maintain observable workflow orchestration systems using DAGs to keep critical data pipelines running reliably.
• Build robust, scalable Python APIs and microservices that power AI-driven insights and customer-facing interfaces.
• Set engineering standards across the stack, including data quality gates, schema evolution strategies, CI/CD automation, and observability.

Job description

Dex is a partner-led company building an AI-powered platform to transform messy data into automated pricing, inventory, and distribution insights. You will own end-to-end data ingestion, workflow orchestration, and backend service architecture from the ground up.

You will partner with founders and ship resilient ingestion pipelines, observable DAG-based workflows, and scalable Python APIs. This role demands ownership, high initiative, and comfort in a fast-moving startup context.