Data Engineer

Location: London, United Kingdom
Work arrangement: Hybrid, with 3–4 days per week in the London office
Employment: Full-time
Compensation: Up to £150,000 per year, depending on experience, plus stock options
Relocation: Visa sponsorship and relocation support available for exceptional international candidates

Milo is an AI-powered data analyst that enables teams to get reliable answers from their business data in minutes. Instead of waiting for dashboards or relying on the few people who understand where every metric lives, teams can connect their data to Milo and explore it through natural-language questions, automated reports, and actionable insights.

Having built the AI analyst, Milo is now developing the underlying data platform: infrastructure built by agents, for agents. The platform will allow AI agents to create pipelines that ingest, clean, reconcile, and structure company data, connecting it to semantic models and ontologies so that it becomes reliable, meaningful, and accessible to both AI agents and traditional analytics tools.

Milo is looking for a highly hands-on Senior Data Engineer to help build this platform from the ground up.

This is not a maintenance role within an established data environment. You will shape the product itself—from the pipeline architecture used by AI agents to the storage, orchestration, and semantic layers that transform raw information into agent-ready data.

The ideal candidate has previously joined a product company and helped build or significantly scale its data platform, warehouse, or pipeline infrastructure. You should be comfortable making architectural decisions independently, explaining the tradeoffs behind them, and remaining actively involved in implementation.

Strong backend or full-stack engineers with substantial data-platform experience may also be considered.

• Build the infrastructure and foundational components that agents use to ingest, clean, transform, and merge data from heterogeneous sources.

• Help design the semantic models and ontology layer that give raw company data meaning and context.

• Design and operate reliable, observable DAG-based data workflows.

• Build data pipelines and transformation systems from the ground up.

• Evaluate and select databases, storage technologies, orchestration tools, and architectural patterns based on product requirements.

• Make large and complex datasets performant and accessible to AI agents, analytics systems, and BI workloads.

• Integrate with databases, enterprise SaaS platforms, APIs, and other external data sources.

• Establish engineering standards around testing, observability, reliability, and data quality.

• Collaborate closely with product and AI engineers to define the data infrastructure required by intelligent agents.

• Remain deeply hands-on with coding, architecture, deployment, and production operations.

• Help set the technical direction of the platform as the engineering team grows.

• 5+ years of professional data engineering, backend engineering, or closely related software engineering experience.

• Experience building a data platform, data warehouse, or major pipeline infrastructure from scratch.

• Meaningful experience working within a product company or owning an internal product over time.

• Strong production-level programming skills, particularly in Python or another relevant backend language.

• Hands-on experience with modern ETL/ELT frameworks such as dbt, Dagster, or comparable tools.

• Experience deploying and operating DAG-based orchestrators such as Airflow.

• A track record of combining and reconciling data from multiple heterogeneous sources.

• Experience working across different storage systems, including relational databases, object storage, and analytical warehouses.

• Experience making large datasets available to BI or analytical systems at scale.

• Familiarity with columnar and analytical storage engines such as ClickHouse, DuckDB, or similar technologies.

• Strong understanding of data modelling, system design, performance, reliability, and observability.

• Ability to make independent architectural decisions and clearly explain the technical and product tradeoffs involved.

• A builder mindset and the drive to operate effectively within a fast-moving startup.

• Willingness to use AI-assisted development tools thoughtfully while maintaining strong independent coding and engineering fundamentals.

• Strong English communication skills.

• Experience designing semantic layers, metadata systems, knowledge graphs, or ontologies.

• Experience building infrastructure used by AI agents or machine learning products.

• Experience integrating with enterprise platforms such as Salesforce or SAP.

• Experience designing autonomous or metadata-driven ingestion and transformation workflows.

• Previous experience as an early or foundational engineer.

• Experience scaling a data platform as its customers, sources, and workloads grew.

Milo is a small, ambitious team working at the intersection of AI, data infrastructure, and business analytics. This is an opportunity to have meaningful influence over the architecture and direction of a new platform instead of inheriting a long-established system.

The team works collaboratively from its London office, where engineers can make decisions quickly and solve problems together. The environment is fast-paced and ownership-heavy, with high expectations for technical judgment, initiative, and execution.

Candidates already based in London or elsewhere in the United Kingdom are preferred.

Milo is also open to exceptional candidates worldwide who are committed to relocating to London. International hires may begin remotely during an initial three-month evaluation period, followed by visa sponsorship and relocation support if both sides decide to proceed.

Once based in London, team members are expected to work from the office approximately three to four days per week.

• Compensation of up to £150,000 per year, depending on experience.

• Generous stock options.

• Visa sponsorship and relocation support for qualifying international candidates.

• A foundational role with direct influence over architecture and product direction.

• The opportunity to build a new category of data infrastructure for AI agents.

• A highly collaborative environment with a technically strong founding team.