At a Glance
- Tasks: Lead and mentor a team of Data Engineers while building scalable data solutions.
- Company: Join a fast-growing AI SaaS business at a pivotal growth stage.
- Benefits: Opportunity to grow into leadership while staying hands-on with technology.
- Other info: Collaborative environment where your ideas are valued and learning is encouraged.
- Why this job: Shape the future of Data Engineering and work on innovative AI products.
- Qualifications: Strong Python and SQL skills, with experience in cloud platforms and ETL processes.
The predicted salary is between 70000 - 90000 £ per year.
Join a fast-growing AI SaaS business where Data Engineering sits at the heart of the platform. This is an opportunity to join at a pivotal stage of the company's growth. As Lead Data Engineer, you'll shape and scale the Data Engineering function, define engineering standards and build a high-performing team, while remaining hands on with the technology that powers innovative AI products. As the business continues to grow, the vision is for this role to evolve into the leadership position responsible for the wider Data Engineering function, making it an excellent opportunity for someone who enjoys leading from the front and wants to grow their career without stepping away from technology.
What you'll be doing:
- Leading, mentoring and growing a team of Data Engineers
- Designing and building scalable data pipelines and cloud based data platforms
- Developing robust ETL and ELT solutions using Python and SQL
- Defining engineering standards, data models and best practice
- Driving CI/CD, automation and modern engineering practices
- Collaborating with AI engineers to productionise machine learning and AI solutions
- Exploring how AI can enhance engineering productivity, quality and delivery
Qualifications:
- Strong experience with Python and SQL
- Expertise building modern data platforms on Azure, AWS or GCP
- Strong ETL and ELT engineering experience
- Data modelling and data warehousing expertise
- CI/CD, Git and engineering best practice
- Previous experience leading, mentoring or developing engineers
Additional responsibilities:
- Build and shape a Data Engineering function from the ground up, with the opportunity to grow into the future Head of Data Engineering as the team expands.
- Stay technically hands on while leading a high performing team
- Work on innovative AI and data products solving real business challenges
- Collaborate with experienced engineers, architects and AI specialists in a supportive environment where ideas are valued and learning is encouraged
If you're looking for a role where you can influence technical direction, build great engineering practices and remain close to the technology, we want to hear from you.
Lead Data Engineer in City of Westminster employer: Datatech Analytics
At Datatech, we pride ourselves on being a dynamic and innovative employer that places Data Engineering at the forefront of our AI SaaS business. Our collaborative work culture fosters creativity and growth, providing ample opportunities for professional development while remaining hands-on with cutting-edge technology. Join us in a supportive environment where your ideas are valued, and you can shape the future of data engineering as we expand our team and capabilities.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer in City of Westminster
✨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 in City of Westminster
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.
