At a Glance
- Tasks: Lead the transformation of data architecture and optimise scalable data pipelines.
- Company: Join a forward-thinking tech company in East London/Essex with a hybrid working model.
- Benefits: Competitive salary up to £75k, flexible working, and opportunities for professional growth.
- Other info: Dynamic role with potential for leadership and mentoring in a collaborative environment.
- Why this job: Make a real impact by modernising data platforms and leading innovative projects.
- Qualifications: Strong SQL skills, experience with Microsoft Fabric, and a passion for data engineering.
The predicted salary is between 63000 - 77000 £ per year.
Hybrid Working - 2-4 days per month in the office (East London / Essex). Salary to £75k.
A Lead Data Engineer is required for a transformational role. With Fabric already in place, the focus is now on maturing the data architectural environment from Bronze through to Gold over the next 12-18 months - improving architecture, data quality, and overall platform capability. This is a hands-on leadership role, acting as the senior technical escalation point while helping shape best practice, refine existing pipelines, and drive data modernisation across a complex data landscape. This is more of a Technical Leadership than people Leadership role, though the director would be happy for someone inclined towards both or that wants to add on the people in time.
Key Responsibilities
- Design, build and optimise scalable data pipelines within Microsoft Fabric (Lakehouse, Data Engineering, Data Warehouse, Data Integration).
- Refine and enhance existing pipelines and architecture to align with best practice.
- Lead the transition of the platform from Bronze to Gold standard.
- Develop and fine-tune complex SQL queries, transformations, and data models.
- Support and troubleshoot data issues impacting reporting (e.g. Power BI refresh failures).
- Take ownership of data quality, governance, and platform reliability.
- Act as the technical escalation point for a team of Data Engineers.
- Lead, mentor, and support a small team (3 engineers) - negotiable if you'd prefer to remain technically oriented.
- Work across multiple data sources (enterprise systems and bespoke applications) feeding into a Lakehouse.
- Engage stakeholders across the business to improve data quality and consistency.
Required Experience
- Strong hands-on SQL expertise, including performance tuning.
- Proven experience with Microsoft Fabric and Synapse (design, architecture, implementation).
- Experience working with Lakehouse architecture and multiple data sources.
- Demonstrable experience modernising data platforms (e.g. Bronze to Gold maturity) or consolidating data into a central platform.
- Strong understanding of data engineering principles, governance, and data quality.
- Experience delivering and supporting production-grade data solutions.
- Ability to act as a senior technical escalation point and lead delivery.
- Strong stakeholder engagement skills, particularly around data quality challenges.
- Microsoft certifications (e.g. DP-600, DP-900).
- Experience managing or mentoring engineers (or readiness to step into leadership).
- Exposure to DevOps / CI-CD practices within data engineering.
- Experience in complex or enterprise environments.
Lead Data Engineer in London employer: Kinetech
Kinetech is an exceptional employer that fosters a dynamic and collaborative work culture, particularly in our East London/Essex offices. We prioritise employee growth through hands-on leadership opportunities and encourage innovation in our data engineering practices, making it a rewarding environment for those looking to advance their careers while contributing to cutting-edge projects.
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We think this is how you could land Lead Data Engineer in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Lead Data Engineer 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!
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 Kinetech, 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 Kinetech. 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 Kinetech
✨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 Kinetech!
✨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.
