At a Glance
- Tasks: Lead the design of real-time data pipelines for an AI-driven property management platform.
- Company: Join LightWork AI, revolutionising the £33B property management market with innovative technology.
- Benefits: Competitive salary plus equity, and the chance to shape the future of data engineering.
- Other info: Exciting opportunity for career growth in a dynamic, early-stage tech environment.
- Why this job: Be a pioneer in AI data engineering and make a significant impact on industry operations.
- Qualifications: 7+ years in data engineering, expert in Python, SQL, and scalable systems.
The predicted salary is between 80000 - 100000 £ per year.
LightWork AI is building the AI-driven operating system for the £33B property management market, featuring an autonomous agent that handles communications and coordination for over 14,000 units.
As the first senior data hire at LightWork AI, you will architect the end-to-end data layer powering Felicity, our autonomous AI agent. You’ll build real-time pipelines and dynamic data models that allow our AI to query live property records, fundamentally transforming how the £33B property management industry operates.
Location: London, UK
Why this role is remarkable:
- Lead greenfield data engineering for an AI platform managing 14,000+ units, reporting to a Head of Engineering who previously built a 140-person data department.
- Own the end-to-end data layer for 'Felicity,' an autonomous agent automating 90% of operations in the £33B property management market.
- Join at a pivotal early stage with meaningful equity and the opportunity to define the technical architecture and long-term data strategy.
What You Will Do:
- Architect and maintain real-time data pipelines (Kafka, Debezium) integrating diverse Property Management Systems like Alto, MRI, and Reapit.
- Design resilient data models and schemas for complex property data, defining how live information is structured and served to the LLM layer.
- Develop knowledge extraction pipelines to pull valuable signals from unstructured sources including emails, legal documents, and PDFs.
The ideal candidate:
- 7+ years of data or backend engineering experience, specifically building scalable distributed systems and real-time data pipelines (Kafka, Spark, or Airflow).
- Expert proficiency in Python and SQL, with deep hands-on experience in PostgreSQL, NoSQL databases, and managing data processing performance at scale.
- Architectural expertise in designing data ingestion and storage frameworks for AI workloads, including vector databases and ML data pipelines.
Lead Data Engineer (+ Equity) at LightWork AI employer: Jack & Jill
LightWork AI is an exceptional employer, offering a unique opportunity to lead innovative data engineering projects within a rapidly growing AI platform in the heart of London. With a strong focus on employee growth and meaningful equity participation, you will be part of a collaborative work culture that values your contributions and empowers you to shape the future of property management technology. Join us at this pivotal stage to make a significant impact while enjoying the vibrant atmosphere of one of the world's most dynamic cities.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer (+ Equity) at LightWork AI
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We think you need these skills to ace Lead Data Engineer (+ Equity) at LightWork AI
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 Jack & Jill, 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 Jack & Jill. 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 Jack & Jill
✨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 Jack & Jill!
✨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.
