01Overview
Senior Data Engineer
KEY: Open to candidates worldwide - we sponsor visas and cover relocation
. You'll need to be based in London and work on-site, but if you're willing to make the move, we'll handle the visa sponsorship and cover the cost of getting you here.
Milo.ai London (UK) On-Site Full-time
Who we are
Milo is an AI analyst that gives teams answers from their data in minutes. No more waiting days for a dashboard or chasing down the one person who knows where the numbers live - Milo connects to your company's data and delivers insight on demand.
Building the agent was just the beginning . We're now moving one level deeper: a data platform built by agents, for agents . On our platform, agents create pipelines that automatically clean a company's data and make it agent-ready by connecting it to a semantic model and an ontology. The result: clean, well-defined, meaning-rich data that any agent - ours or anyone else's - can reliably reason over. We believe this is the next foundational layer of the AI stack, and we're building it now.
The role
As a Senior Data Engineer, you'll sit at the forefront of this new platform. This isn't a maintenance role on an established system - you'll be deeply involved in shaping the product itself: the pipeline architecture agents build on, the semantic layer that gives data meaning, and the standards for what "agent-ready data" means.
You'll build the infrastructure that lets agents autonomously create pipelines - ingesting, cleaning, and unifying data from a wide range of sources, then connecting it to a semantic model and ontology so it's fast, queryable, and meaningful for both AI agents and traditional BI workloads.
What you'll do
- Build the pipeline infrastructure and primitives that agents use to autonomously ingest, clean, and merge data from diverse sources
- Shape the semantic model and ontology layer that turns raw company data into agent-ready data
- Design and operate robust DAG-based orchestration for reliable, observable, agent-driven workflows
- Make large volumes of data performant and accessible for agents and analytical/BI workloads alike
- Work closely with product and AI engineering to define what agents need from data infrastructure
- Help set the engineering standards and best practices as the team grows
What we're looking for
- 5+ years of data engineering experience , ideally including time at a fast-moving product company
- Strong hands-on experience with modern ETL/ELT tooling such as dbt, Dagster, or similar
- A track record of building data pipelines that merge and reconcile data from multiple heterogeneous sources
- High proficiency in Python (and/or other relevant languages)
- Experience deploying and operating DAG orchestrators such as Airflow
- Familiarity with a variety of storage systems
- relational, object storage, warehouses, and beyond
- Experience making large datasets accessible to BI systems at scale
- Hands-on experience with columnar storage engines such as ClickHouse or DuckDB
Bonus points
- Experience integrating with enterprise SaaS APIs (e.g. Salesforce, SAP)
What we offer
- Compensation: 70,000 150,000 , depending on experience
- Generous Stock Options
- A foundational role on a new product with real influence over architecture and direction
- A small, ambitious team building at the frontier of AI and data infrastructure .
