At a Glance
- Tasks: Build cutting-edge data pipelines and shape the future of AI-driven data infrastructure.
- Company: Join Milo.ai, a pioneering AI analyst company transforming data insights.
- Benefits: Competitive salary, generous stock options, and a chance to influence product direction.
- Other info: Work in a small, ambitious team with excellent growth opportunities.
- Why this job: Be at the forefront of AI innovation and make a real impact on data accessibility.
- Qualifications: 5+ years in data engineering with strong ETL/ELT experience and Python skills.
The predicted salary is between 70000 - 150000 £ per year.
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.
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.
Senior Data Engineer in London employer: Autonomous Minds
Milo.ai is an exceptional employer for Senior Data Engineers, offering a unique opportunity to shape the future of AI-driven data infrastructure in the vibrant tech hub of London. With a focus on innovation and collaboration, employees benefit from generous stock options, a competitive salary range, and the chance to work within a small, ambitious team that values each member's contributions. The company fosters a dynamic work culture that encourages professional growth and creativity, making it an ideal place for those looking to make a meaningful impact in their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Autonomous Minds!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Engineer at Autonomous Minds.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Autonomous Minds.
✨Apply Directly through Our Website
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We think you need these skills to ace Senior Data Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Autonomous Minds, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Autonomous Minds. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Autonomous Minds
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Autonomous Minds!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
