At a Glance
- Tasks: Lead the development of data infrastructure for an innovative AI assistant in property management.
- Company: Join Smart Working, a top-rated remote-first workplace that values your growth.
- Benefits: Enjoy a supportive community, competitive salary, and opportunities for personal and professional development.
- Other info: Be part of a dynamic environment with excellent career growth potential.
- Why this job: Make a real impact by shaping data architecture and leading a growing team.
- Qualifications: 7+ years in data engineering, strong skills in data pipelines and distributed systems.
The predicted salary is between 72000 - 88000 £ per year.
About Smart Working
At Smart Working, we believe your job should not only look right on paper but also feel right every day.
This isn’t just another remote opportunity - it’s about finding where you truly belong, no matter where you are.
From day one, you’re welcomed into a genuine community that values your growth and well-being.
Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles.
We help you discover meaningful work with teams that invest in your success, where you’re empowered to grow personally and professionally.
Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world.
About the Role
As a Lead Data Engineer, you will build and lead the data infrastructure powering an intelligent AI assistant that automates operational workloads for property managers, letting agents and build-to-rent teams.
The platform handles communications, compliance, maintenance coordination and scheduling, helping property businesses operate with the efficiency of modern digital platforms.
You will architect and scale the data systems behind the AI products, covering real-time data pipelines, analytics infrastructure, vector databases and machine learning data workflows.
Working closely with AI engineers, backend engineers, product teams, founders and product leadership, you will ensure the platform can process large volumes of operational data reliably, efficiently and intelligently.
As the first senior data hire, you will play a key role in defining the data architecture, technology stack, engineering standards and ways of working.
You will also help shape the data team, establishing its culture and hiring bar as the function grows.
Responsibilities
- Architect and build scalable data pipelines and infrastructure to support AI and product systems.
- Design and maintain data ingestion, transformation and storage architectures for operational and AI workloads.
- Develop and manage batch and real-time data pipelines.
- Build and optimise systems for vector search, retrieval and machine learning data pipelines.
- Ensure data reliability, security and governance across the platform.
- Collaborate with AI and backend engineering teams to support training, inference and product features.
- Implement monitoring, observability and data quality frameworks.
- Optimise the performance of large-scale datasets and query systems.
- Contribute to technical architecture decisions and long-term data strategy.
- Act as the founding data hire, defining culture, standards and the hiring bar for the data function as it scales.
- Partner directly with founders and product leadership to translate data capabilities into product decisions.
Requirements
- 7+ years of professional experience, with the majority of that experience in dedicated data engineering roles.
- Strong experience designing and building data pipelines and distributed data systems.
- Experience working with relational databases, with Postgre SQL preferred, although My SQL or similar is acceptable.
- Experience working with No SQL databases.
- Experience with vector databases used in modern AI systems.
- Strong programming experience in Python.
- Demonstrated ability to make and justify architectural decisions, rather than only implementing them.
- Experience building scalable backend systems.
- Experience designing data models and storage architectures.
- Strong understanding of data processing performance and optimisation.
- Experience with some of the following data frameworks and infrastructure technologies is highly desirable: Apache Spark, Apache Airflow, Kafka, and Elasticsearch or Open Search.
- Experience with relevant database technologies is highly desirable, including Postgre SQL, Mongo DB, and vector databases such as Qdrant, Milvus or pgvector.
- Experience with Python data-processing libraries such as Pandas or Polars is highly desirable.
- Nice to Have
- Experience working on AI or machine learning platforms.
- Familiarity with stream processing and event-driven architectures.
- Experience with cloud infrastructure such as GCP, AWS or Azure.
- Experience working in high-growth startups or early-stage companies.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information.
These tools assist our recruitment team but do not replace human judgment.
Final hiring decisions are ultimately made by humans.
If you would like more information about how your data is processed, please contact us.
Lead Data Engineer (Contract, Full-Time) [HR208] (UK) in London employer: Smart Working Solutions
Smart Working Solutions is an excellent employer, offering a supportive remote work culture that prioritises employee well-being while providing ample opportunities for career growth. As a Senior Data Engineer, you'll be part of a dynamic team working with cutting-edge technologies like AWS and Snowflake, making a meaningful impact across multiple iGaming brands.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer (Contract, Full-Time) [HR208] (UK) in London
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We think you need these skills to ace Lead Data Engineer (Contract, Full-Time) [HR208] (UK) 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!
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Craft a Tailored Cover Letter:For a full-time role at Smart Working Solutions, 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 Smart Working Solutions. 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 Smart Working Solutions
✨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!
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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 Smart Working Solutions!
✨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.
