At a Glance
- Tasks: Lead and optimise data pipelines, ensuring top-notch data quality and governance.
- Company: Join a forward-thinking company transforming data landscapes in East London/Essex.
- Benefits: Competitive salary up to £75k, hybrid working, and opportunities for professional growth.
- Other info: Mentor a small team and engage with stakeholders to enhance data quality.
- Why this job: Be at the forefront of data modernisation and make a real impact on business decisions.
- Qualifications: Strong SQL skills and experience with Microsoft Fabric and data engineering principles.
The predicted salary is between 75000 - 75000 € per year.
A Lead Data Engineer is required for a transformational role. With Fabric already in place, the focus is now on maturing the 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.
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)
- 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)
Desirable Skills
- 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
Interviews are planned for May. Please apply today for an immediate CV review.
Lead Data Engineer employer: Kinetech
Kinetech is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Lead Data Engineer role. With a focus on employee growth and development, we offer opportunities to lead transformative projects in a hybrid working environment, allowing for flexibility while being part of a dynamic team in East London/Essex. Our commitment to data excellence and modernisation ensures that you will be at the forefront of cutting-edge technology, making a meaningful impact within the organisation.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Microsoft Fabric. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your best data pipelines and SQL queries. When you get that interview, having tangible examples will help you stand out as a hands-on leader.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on your SQL performance tuning and data governance principles. We recommend mock interviews with friends or using online platforms to simulate the experience.
✨Tip Number 4
Apply through our website! It’s the quickest way to get noticed. Plus, we love seeing candidates who take the initiative to engage directly with us. Don’t miss out on the chance to land that Lead Data Engineer role!
We think you need these skills to ace Lead Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Lead Data Engineer role. Highlight your hands-on SQL expertise and any experience with Microsoft Fabric, as these are key for us.
Showcase Your Projects:Include specific examples of projects where you've modernised data platforms or improved data quality. We love seeing how you've tackled challenges in complex environments!
Be Clear and Concise:When writing your application, keep it straightforward. Use bullet points for easy reading and make sure to clearly outline your responsibilities and achievements in previous roles.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any updates!
How to prepare for a job interview at Kinetech
✨Know Your Data Inside Out
Make sure you’re well-versed in the specifics of data engineering principles, especially around SQL and Microsoft Fabric. Brush up on your knowledge of Lakehouse architecture and be ready to discuss how you've modernised data platforms in the past.
✨Showcase Your Leadership Skills
Since this role involves leading a small team, be prepared to share examples of how you've mentored or supported other engineers. Highlight any experiences where you acted as a technical escalation point and how you engaged stakeholders to improve data quality.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions about data pipelines, performance tuning, and troubleshooting. Practise explaining complex SQL queries and transformations clearly, as you may need to demonstrate your thought process during the interview.
✨Engage with Real-World Scenarios
Think of specific challenges you've faced in previous roles, particularly around data quality and governance. Be ready to discuss how you approached these issues and what solutions you implemented, as this will show your problem-solving skills and practical experience.
