At a Glance
- Tasks: Design and build scalable data platforms for high-quality analytics and data-driven products.
- Company: Leading engineering firm in London with a focus on innovation.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Join a dynamic team with a commitment to excellence and continuous improvement.
- Why this job: Lead cutting-edge data projects and make a significant impact in the tech industry.
- Qualifications: Experience in data engineering, strong SQL, Python/Scala skills, and cloud expertise.
The predicted salary is between 130000 - 130000 £ per year.
We are seeking a Lead Data Engineer to design, build and own scalable data platforms that enable high-quality analytics, reporting and data-driven products. You will provide technical leadership across the data engineering function, set standards for reliability and governance, and partner with stakeholders to deliver trusted datasets and pipelines.
Key Responsibilities
- Lead the architecture and delivery of modern data platforms (lakehouse/warehouse) and robust ETL/ELT pipelines.
- Define engineering standards for code quality, testing, documentation, security and operational excellence.
- Own data modelling (dimensional, Data Vault and domain-oriented approaches) and optimise performance and cost.
- Implement orchestration, monitoring and alerting for data workflows; manage SLAs and incident response.
- Drive data governance: lineage, catalogue, access controls, retention policies and GDPR-aligned practices.
- Collaborate with analytics, software and platform teams to deliver reusable data products and APIs.
- Mentor engineers, conduct code reviews, and contribute to hiring and capability development.
Required Skills & Experience
- Significant experience in data engineering, including leading teams or major technical initiatives.
- Expert SQL and strong programming skills in Python and/or Scala.
- Cloud data engineering experience (AWS, Azure or GCP), including object storage, compute and managed data services.
- Strong experience with modern data warehousing/lakehouse tools (e.g., Snowflake, BigQuery, Redshift, Databricks).
- Hands-on orchestration experience (e.g., Airflow, Dagster, Prefect) and CI/CD for data pipelines.
- Experience with streaming and event-driven data (e.g., Kafka, Kinesis, Pub/Sub) is highly desirable.
- Proficiency with infrastructure as code (e.g., Terraform, CloudFormation) and containerisation (Docker; Kubernetes beneficial).
- Strong understanding of data quality frameworks, testing (unit/integration), and observability.
- Excellent stakeholder management and communication skills, able to translate requirements into technical solutions.
Qualifications
- Bachelor's degree in Computer Science, Engineering, Mathematics or a related discipline (or equivalent experience).
- Relevant cloud or data certifications are advantageous.
What You'll Bring
- A pragmatic, delivery-focused mindset with a commitment to high standards.
- Ability to lead by example, coach others and build effective engineering practices.
- Curiosity, accountability and a continuous improvement approach.
Lead Data Engineer in London employer: Source Group International
As a Lead Data Engineer in London, you will join a forward-thinking company that prioritises innovation and employee development. With a strong emphasis on collaboration and mentorship, the work culture fosters continuous learning and growth, while competitive salaries and comprehensive benefits ensure a rewarding experience. The vibrant London location offers unique networking opportunities and access to a diverse tech community, making it an excellent place for professionals seeking meaningful and impactful work.
Contact Details:
Source Group International Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer in London
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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!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Source Group International. 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 Source Group International
✨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!
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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 Source Group International!
✨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.
