At a Glance
- Tasks: Lead and mentor a team of Data Engineers while designing scalable data pipelines.
- Company: Fast-growing AI SaaS business at the forefront of data engineering.
- Benefits: Competitive salary, hybrid work model, and opportunities for career growth.
- Other info: Join a supportive environment where your ideas are valued and learning is encouraged.
- Why this job: Shape the future of data engineering and work on innovative AI solutions.
- Qualifications: Strong experience in Python, SQL, and cloud platforms like AWS or Azure.
The predicted salary is between 95000 - 95000 £ per year.
Salary: £95,000 - £95,000 per year
Requirements
- Strong experience with Python and SQL
- Experience building modern data platforms on Azure, AWS, or GCP
- Strong ETL and ELT engineering experience
- Experience with data modelling and data warehousing
- Experience with CI/CD, Git, and engineering best practice
- Previous experience leading, mentoring, or developing engineers
Responsibilities
- Lead, mentor, and grow a team of Data Engineers
- Design and build scalable data pipelines and cloud-based data platforms
- Develop robust ETL and ELT solutions using Python and SQL
- Define engineering standards, data models, and best practice
- Drive CI/CD, automation, and modern engineering practices
- Collaborate with AI engineers to productionise machine learning and AI solutions
- Explore how AI can enhance engineering productivity, quality, and delivery
Technologies
- AI
- AWS
- Azure
- CI/CD
- Cloud
- ETL
- GCP
- Git
- Machine Learning
- Python
- SQL
We are a fast-growing AI SaaS business where Data Engineering sits at the heart of our platform. This is a hybrid role based in London, with Monday to Thursday in the office and Friday working from home. We offer a salary of £85,000-£95,000 depending on experience. You will join us at a pivotal stage of our growth, with the opportunity to shape and scale our Data Engineering function, influence technical direction, and grow into a future Head of Data Engineering role as the team expands. We provide a supportive environment where ideas are valued and learning is encouraged, and you will work alongside experienced engineers, architects, and AI specialists on innovative AI and data products that solve real business challenges.
Lead Data Engineer employer: Datatech Analytics
Join our fast-growing AI SaaS business as a Lead Data Engineer, where you'll play a crucial role in shaping our data engineering function in a supportive and innovative environment. With a hybrid work model based in London, we offer competitive salaries and ample opportunities for professional growth, including the potential to advance to a Head of Data Engineering role. Collaborate with talented engineers and AI specialists to develop cutting-edge solutions that address real-world challenges while enjoying a culture that values your ideas and encourages continuous learning.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer
✨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 Datatech Analytics!
✨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 Lead Data Engineer at Datatech Analytics.
✨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 Datatech Analytics.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Engineer at Datatech Analytics, 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 Lead Data Engineer
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 Datatech Analytics, 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 Datatech Analytics. 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 Datatech Analytics
✨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 Datatech Analytics!
✨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.
