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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 .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.