At a Glance
- Tasks: Design and maintain robust data pipelines and deploy advanced AI/ML workloads.
- Company: Fast-scaling workforce management platform disrupting the hospitality sector.
- Benefits: Competitive salary, remote work options, and opportunities for mentorship.
- Other info: Join a dynamic team with a direct impact on major hospitality brands.
- Why this job: Take ownership of a cutting-edge AWS-native data platform and influence architectural decisions.
- Qualifications: Expert Python and SQL skills with MLOps experience in a cloud environment.
The predicted salary is between 60000 - 80000 £ per year.
Join a high-growth scale‑up as the technical backbone of a sophisticated data platform. You will own the full data lifecycle, from designing robust ETL/ELT pipelines in Airflow to deploying advanced AI/ML workloads. This role bridges the gap between data engineering and MLOps, ensuring reliability as the platform expands to thousands of restaurant partners.
Location: London, UK
Why this role is remarkable:
- Take technical ownership of a production AWS‑native data platform supporting complex workforce logistics for major hospitality brands.
- Work at the cutting edge of AI deployment, moving beyond traditional forecasting to implement agentic architectures and LLM‑based systems.
- High‑impact position with a direct path to architectural influence, freeing leadership from firefighting while mentoring a growing team of juniors.
What You Will Do:
- Design, build, and maintain mission‑critical ETL/ELT pipelines using Airflow (MWAA) and AWS‑native tools like Athena, Redshift, and S3.
- Deploy and serve diverse ML workloads including traditional SageMaker models and agentic chatbots using Bedrock and Lambda.
- Drive infrastructure‑as‑code (IaC) adoption and operational best practices to ensure high availability and data quality across the platform.
The ideal candidate:
- Expert‑level Python and SQL skills with proven experience building production‑grade data pipelines and handling incident response.
- Hands‑on MLOps background with specific experience packaging, versioning, and monitoring ML models in a cloud environment.
- Deep familiarity with the AWS ecosystem, specifically Lambda, SageMaker, and RDS, coupled with a strong CI/CD and DevOps mindset.
Senior Data Engineer at fast-scaling workforce management platform employer: Jack & Jill
Join a dynamic and innovative workforce management platform that is revolutionising the hospitality sector in London. As a Senior Data Engineer, you will thrive in a collaborative work culture that prioritises employee growth and mentorship, while enjoying the unique opportunity to influence architectural decisions and work with cutting-edge AI technologies. With a focus on high-impact projects and a commitment to operational excellence, this role offers a rewarding environment for those looking to make a significant contribution to a fast-scaling company.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer at fast-scaling workforce management platform
✨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 Jack & Jill!
✨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 fast-scaling workforce management platform at Jack & Jill.
✨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 Jack & Jill.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Engineer at fast-scaling workforce management platform at Jack & Jill, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Engineer at fast-scaling workforce management platform
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.
